{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# One step multivariate model\n",
    "\n",
    "In this notebook, we demonstrate how to:\n",
    "- prepare time series data for training a RNN forecasting model\n",
    "- get data in the required shape for the keras API\n",
    "- implement a RNN model in keras to predict the next step ahead (time *t+1*) in the time series. This model uses recent values of temperature, as well as load, as the model input.\n",
    "- enable early stopping to reduce the likelihood of model overfitting\n",
    "- evaluate the model on a test dataset\n",
    "\n",
    "The data in this example is taken from the GEFCom2014 forecasting competition<sup>1</sup>. It consists of 3 years of hourly electricity load and temperature values between 2012 and 2014. The task is to forecast future values of electricity load. In this example, we show how to forecast one time step ahead, using historical load and temperature data.\n",
    "\n",
    "<sup>1</sup>Tao Hong, Pierre Pinson, Shu Fan, Hamidreza Zareipour, Alberto Troccoli and Rob J. Hyndman, \"Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond\", International Journal of Forecasting, vol.32, no.3, pp 896-913, July-September, 2016."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('..')\n",
    "import os\n",
    "import warnings\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import datetime as dt\n",
    "from collections import UserDict\n",
    "from IPython.display import Image\n",
    "%matplotlib inline\n",
    "\n",
    "from common.utils import load_data, mape, TimeSeriesTensor, create_evaluation_df\n",
    "\n",
    "pd.options.display.float_format = '{:,.2f}'.format\n",
    "np.set_printoptions(precision=2)\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load data into Pandas dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>load</th>\n",
       "      <th>temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-01-01 00:00:00</th>\n",
       "      <td>2,698.00</td>\n",
       "      <td>32.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 01:00:00</th>\n",
       "      <td>2,558.00</td>\n",
       "      <td>32.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 02:00:00</th>\n",
       "      <td>2,444.00</td>\n",
       "      <td>30.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 03:00:00</th>\n",
       "      <td>2,402.00</td>\n",
       "      <td>31.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 04:00:00</th>\n",
       "      <td>2,403.00</td>\n",
       "      <td>32.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        load  temp\n",
       "2012-01-01 00:00:00 2,698.00 32.00\n",
       "2012-01-01 01:00:00 2,558.00 32.67\n",
       "2012-01-01 02:00:00 2,444.00 30.00\n",
       "2012-01-01 03:00:00 2,402.00 31.00\n",
       "2012-01-01 04:00:00 2,403.00 32.00"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_dir = '../data/'\n",
    "energy = load_data(data_dir)\n",
    "energy.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "valid_start_dt = '2014-09-01 00:00:00'\n",
    "test_start_dt = '2014-11-01 00:00:00'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot all load and temperature data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "energy.plot(y=['load', 'temp'], subplots=True, figsize=(15, 8), fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load and temperature in first week of July 2014"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "energy['2014-07-01':'2014-07-07'].plot(y=['load', 'temp'], subplots=True, figsize=(15, 8), fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = 6\n",
    "HORIZON = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create training dataset with *load* and *temp* features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = energy.copy()[energy.index < valid_start_dt][['load', 'temp']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fit a scaler for the *y* values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MinMaxScaler(copy=True, feature_range=(0, 1))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "\n",
    "y_scaler = MinMaxScaler()\n",
    "y_scaler.fit(train[['load']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Also scale the input features data (*load* and *temp* values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_scaler = MinMaxScaler()\n",
    "train[['load', 'temp']] = X_scaler.fit_transform(train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the TimeSeriesTensor convenience class to:\n",
    "1. Shift the values of the time series to create a Pandas dataframe containing all the data for a single training example\n",
    "2. Discard any samples with missing values\n",
    "3. Transform this Pandas dataframe into a numpy array of shape (samples, time steps, features) for input into Keras\n",
    "\n",
    "The class takes the following parameters:\n",
    "\n",
    "- **dataset**: original time series\n",
    "- **H**: the forecast horizon\n",
    "- **tensor_structure**: a dictionary discribing the tensor structure in the form { 'tensor_name' : (range(max_backward_shift, max_forward_shift), [feature, feature, ...] ) }\n",
    "- **freq**: time series frequency\n",
    "- **drop_incomplete**: (Boolean) whether to drop incomplete samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "tensor_structure = {'X':(range(-T+1, 1), ['load', 'temp'])}\n",
    "train_inputs = TimeSeriesTensor(dataset=train,\n",
    "                            target='load',\n",
    "                            H=HORIZON,\n",
    "                            tensor_structure=tensor_structure,\n",
    "                            freq='H',\n",
    "                            drop_incomplete=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>tensor</th>\n",
       "      <th>target</th>\n",
       "      <th colspan=\"12\" halign=\"left\">X</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>feature</th>\n",
       "      <th>y</th>\n",
       "      <th colspan=\"6\" halign=\"left\">load</th>\n",
       "      <th colspan=\"6\" halign=\"left\">temp</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time step</th>\n",
       "      <th>t+1</th>\n",
       "      <th>t-5</th>\n",
       "      <th>t-4</th>\n",
       "      <th>t-3</th>\n",
       "      <th>t-2</th>\n",
       "      <th>t-1</th>\n",
       "      <th>t</th>\n",
       "      <th>t-5</th>\n",
       "      <th>t-4</th>\n",
       "      <th>t-3</th>\n",
       "      <th>t-2</th>\n",
       "      <th>t-1</th>\n",
       "      <th>t</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-01-01 05:00:00</th>\n",
       "      <td>0.18</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 06:00:00</th>\n",
       "      <td>0.23</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 07:00:00</th>\n",
       "      <td>0.29</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 08:00:00</th>\n",
       "      <td>0.35</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 09:00:00</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.42</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 10:00:00</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 11:00:00</th>\n",
       "      <td>0.37</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.40</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 12:00:00</th>\n",
       "      <td>0.36</td>\n",
       "      <td>0.23</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 13:00:00</th>\n",
       "      <td>0.35</td>\n",
       "      <td>0.29</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01 14:00:00</th>\n",
       "      <td>0.36</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.52</td>\n",
       "      <td>0.54</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "tensor              target    X                                               \\\n",
       "feature                  y load                          temp                  \n",
       "time step              t+1  t-5  t-4  t-3  t-2  t-1    t  t-5  t-4  t-3  t-2   \n",
       "2012-01-01 05:00:00   0.18 0.22 0.18 0.14 0.13 0.13 0.15 0.42 0.43 0.40 0.41   \n",
       "2012-01-01 06:00:00   0.23 0.18 0.14 0.13 0.13 0.15 0.18 0.43 0.40 0.41 0.42   \n",
       "2012-01-01 07:00:00   0.29 0.14 0.13 0.13 0.15 0.18 0.23 0.40 0.41 0.42 0.41   \n",
       "2012-01-01 08:00:00   0.35 0.13 0.13 0.15 0.18 0.23 0.29 0.41 0.42 0.41 0.40   \n",
       "2012-01-01 09:00:00   0.37 0.13 0.15 0.18 0.23 0.29 0.35 0.42 0.41 0.40 0.39   \n",
       "2012-01-01 10:00:00   0.37 0.15 0.18 0.23 0.29 0.35 0.37 0.41 0.40 0.39 0.39   \n",
       "2012-01-01 11:00:00   0.37 0.18 0.23 0.29 0.35 0.37 0.37 0.40 0.39 0.39 0.43   \n",
       "2012-01-01 12:00:00   0.36 0.23 0.29 0.35 0.37 0.37 0.37 0.39 0.39 0.43 0.46   \n",
       "2012-01-01 13:00:00   0.35 0.29 0.35 0.37 0.37 0.37 0.36 0.39 0.43 0.46 0.50   \n",
       "2012-01-01 14:00:00   0.36 0.35 0.37 0.37 0.37 0.36 0.35 0.43 0.46 0.50 0.53   \n",
       "\n",
       "tensor                         \n",
       "feature                        \n",
       "time step            t-1    t  \n",
       "2012-01-01 05:00:00 0.42 0.41  \n",
       "2012-01-01 06:00:00 0.41 0.40  \n",
       "2012-01-01 07:00:00 0.40 0.39  \n",
       "2012-01-01 08:00:00 0.39 0.39  \n",
       "2012-01-01 09:00:00 0.39 0.43  \n",
       "2012-01-01 10:00:00 0.43 0.46  \n",
       "2012-01-01 11:00:00 0.46 0.50  \n",
       "2012-01-01 12:00:00 0.50 0.53  \n",
       "2012-01-01 13:00:00 0.53 0.52  \n",
       "2012-01-01 14:00:00 0.52 0.54  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_inputs.dataframe.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(23370, 6, 2)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_inputs['X'].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[0.22, 0.42],\n",
       "        [0.18, 0.43],\n",
       "        [0.14, 0.4 ],\n",
       "        [0.13, 0.41],\n",
       "        [0.13, 0.42],\n",
       "        [0.15, 0.41]],\n",
       "\n",
       "       [[0.18, 0.43],\n",
       "        [0.14, 0.4 ],\n",
       "        [0.13, 0.41],\n",
       "        [0.13, 0.42],\n",
       "        [0.15, 0.41],\n",
       "        [0.18, 0.4 ]],\n",
       "\n",
       "       [[0.14, 0.4 ],\n",
       "        [0.13, 0.41],\n",
       "        [0.13, 0.42],\n",
       "        [0.15, 0.41],\n",
       "        [0.18, 0.4 ],\n",
       "        [0.23, 0.39]]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_inputs['X'][:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(23370, 1)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_inputs['target'].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.18],\n",
       "       [0.23],\n",
       "       [0.29]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_inputs['target'][:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "look_back_dt = dt.datetime.strptime(valid_start_dt, '%Y-%m-%d %H:%M:%S') - dt.timedelta(hours=T-1)\n",
    "valid = energy.copy()[(energy.index >=look_back_dt) & (energy.index < test_start_dt)][['load', 'temp']]\n",
    "valid[['load', 'temp']] = X_scaler.transform(valid)\n",
    "valid_inputs = TimeSeriesTensor(valid, 'load', HORIZON, tensor_structure)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implement the RNN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will implement a simple RNN forecasting model with the following structure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Hfcex0LF256LH55X5jUaupE/+Jf1xhFaLbu3f5z/rsl1LvMexkOE+EEv1J/9X/yxQOJ0DrcdfvmeZ98QrZoQv/gOJP2kzKoIMMI9rsehSvYm3uneyvmNXzHD/Tk1tSxz03/q1bN7gvGPWFuA/FNlG+O/tre0ztRkYRd6Af6/YbygyxbX3rAqS2//wTG1KRWhoaPiPeDzerdWiWbl18avKMY65cP/+XtmfMPtb+83NzS+TPvivSCTyVBfy+nJ9Y2NjTGcX1ar+9rPK9XxZs2PxZm0GkDt3yYCcxHt8J1kpww00qf7FU7RZNW9TMO/w7oHEQ75jVcpwA9zK7ckXarMgOvsS23zHqpSxThKCpTvnP0ubVPNSW5InXnH7pd5jVYb4qzYLYs2ORds9x6jk0bUt+bi77labVdM6NnccW4jLBPONNTs6gu6+5Je0WUB2OvuTp5frXVimuPLOSwPLX3Aphc6+5OLOAl4nVoiQF4A7tHk1y/23wndsyhmp/uR8bV7N6upPdPiOTTlj3eDiYM225S/QJtak1b2X1Ls3W77jU65wr3epvsSvtYk1qbO3/VzfsSlrDCS2aPOA8enctug73pPJQPTsXRa4d4ra1Jqyduei9b5jYiG6tncc9Gb31WzVbck63zGxEN07Og76IyvVLNWbuMl3TCyE+9Lkqr7FL9Gm1hR5I36O23/fcSl7DMhY1pdcok2tKZ29iYT3mFiIvsRB734CDFvd1z7dexIZiqvuWlFzn8h29rWv8B0LS7Fmx6KDfkO9Gi27rf1FvmNhKdZsS7Rqc2tGV3/7j3zHwlKs27UkWH7rH5+qTa4Jq7cn31iKLwnlE+4T2a7+ZFnullEuK/rbZ/qOhaVI9bdv1OYCfiv+sfDZ7pNO3wlkMH6vza56Xb3J/7du0PbA7yIc/AeSn9Jm14RUf+Jx37GwFC5Z6uxP1syPCXT2t7/UeqI0FO5+wNrsmuDuv+s7DvaivaZ+tEb29wn/cbAT4d0LetuatcmoRbFYrF5ie2Njo/deeV197d/ynTwWw71IJavkdk9Tp059oft1HOmX9+ukEWSAudp3DCyGvEjdqc2uePJcmR2Px3ulX16lk0bo6m8zexnB6JB+Oeh9qiuJ9Mks6RN3v8wf19XVHamTh6W2JX/sOwYWw705rabLo6RvPtfS0uLuof3VOXPmjLi/9Kr+jjdXwptxF+H9fgeSH9GmVzTpkw/Ic+VReVzi7nCgk4d1bls0zXcMLIa86btWm41a5u75J4PM79xgIyf1R3Wyu4as33fiWAz3qV/37iXP1aZXjaampo9JQvuI9M9vpX/CFzfZ3/tH77/VkGTJ/TRy1ZH++MOMGTPc88X9mzG8MbcMqGt8x8Bk9CWedG2uNvpLX7dIUnuXvFC/2U3r7Gvf4T0GBsONY5LcPT/cmSqjP2ixTfrn7+5WUZ3bkue6O834joPNaL9Gd6VquDcW0ifup2sDl9y6aTKO9fj331648yfcEWRPBsh2iQtdyAtZUieHpO5+JSicJ9Ghk0MyrzXTejLt4qF5Em06OSTLXpQ2b8S3jNOmuxj+t/qkSZOOGjVv+Gcc5cR91qh5/+tuoSWPZ7lPNaaeNvVnXf3lv21TNjH7o2e4m3MP75MMlMOfzMrxm5c+TyeHpD5/aLo7zjo5JPW2oXkSF+vkkMwb/ntSXqCTQzKtI23eQp0ckmnJoXkSI34hZ9Q2h88PSWbf5n7a9rRTpi5Z+teLzP+rZyjcFzZOnnTK79L2d/S5m34sLtHJIakPH0OJ0c+H4fXcMdPJIZk2/NyUyOa5uWBonmebw89Ntw2dHH466z41lxeA8yVZ6vMdA4vh7uzx/neffLa0//MaX9NdCsn+fC7TPKmfMhRyPEbc6i59nsRpOjmUPk+2X6eTQ6PmTdbJzkQ53i8YiilTpgwneO6nKtPnyXruTaxb/sPuDbnUz3PLScL+sO8YWI2V/6zO29RJfx0m/ftdOWeekPjCZXuW/tAl7b5jYDGkrVX5rXjpi5nTp09/Uh7nu+dU50DiVt/+W4yr715JElvr3MAvA8saiXskJunkUFd/coPvxLEYLllau3Np1dwL070Bkf74lftZQXn8mE4OyYvybt8xsBjyrv4xbXZVkDd47qefr5THXfX19aOeL4mLfcfAYqT62u/SZlc892ZVniNLJf4lcYpOHib7utZ3DCyG+53/ru3JivoRhIOR58mrJLZKv/xDHkdcttbZ33a6hfuPjidcsp3qb/+dNr2inXHGGU+RN3qr5bX/YRnLDvihhO6+9p/7joHFkOf2Lm02apFeo5TxN4pTvYkG34ljMdwnS3ODuYdo0yuefqrkJclS0ncMLEb3tuQObXZVOOmkk0Zc15cutaX1ON8xsBjdOxbVzP0vu25LvL9SPvFzv0Ovza4JLmn3HQdr4f5t3bF5c8l+2rWcOjo6jvAdA5vR8UNtNuBXKdcsdQ20v1ObXBMqYfB3X4ZY29vxNG1yTZD9vmP0cbAW7teqqukN33h09rc/6jsWliL8tG8geaI2uSZ097f/qhLeYKT62/+mTa4Jq3vbb/MdB0vhvhSozQUy67qt/UU9ty/3nkRWYnVvoui/521N59bkVPdLP77jYSHcC9Pq3rafaHNrirzxe9J3TCyE+036VX3tUW1qzXD/or/6rhXeY2IlugY6LtDm1pQ1Oxf92Xc8rET39o6avLH+2h2LzH734rLdS2UcS7xXmwocXGpL+yuu2GszkU0NJC/XZtac1X3J6dZ+qtFFmMD2J36pzaxJa3Ys2uc7NuUMN/Cn+pIjruOtJZf2tj3vmrtXeo9N+aO2fxJYxrHN/uNS3pBE7l/axJrUZfAN+RW3L6+5/1igAOZtmne4DLRmbu3kvsiV6mubrc2rWak7W4/rHEiaucG+u4SgcyDxX9q8mpbqb9/rO0blCHcf5dSOJSdo02qavDD/3XeMyhFrdy4KVvW3jbhTQ61K9SXmmvmi10AiSPUmNmjTapqlL3h3DSSfrLVftUOBrdrWcdKVd5b333JyIv9lQpD5C2m1aNXWhf+ztoyXF4TXtfUlFmlzoJbcvOC563aVr1/CX7Xpa/ueNgdq1baFL7/yjvKOY6mB5FptDtKs3bG4rLeqWze45NGOoKMmvsQ1XisGVxxz+Z7y/Xqnu3RudW97Tf36I4qsW5LZUp7ULkmSv7msp2fuYdoEeEgi2VLKZDb8gllf4gf655HByh0LX9VTwktyetxzs6/9S/rnkcGK/sWv7S7hlyT3/6cieWFHR8eh2gR4uP/8pfoSfw3fHHuOYzFizY6OR5Jbks/RJsDjyoElx5fyV9Yu373M3UZrjv55oPB6+i86yv0b6Jp7VnlPwnzC3Rmhe3vH4JrtyTfqn8M4dW3+wzNTWxMLi/FGY/+ne+1/7trZ/iL9cxgn94Miq/sTX7iqCP/NuExeXKRfrump0l98KqaOzR1HrN7a9n/F+C9T+AZ8e/L2NVsvYRzLwartiffKG8BHfMc23+jZu2xf50D7h/RPYZyGxjF3farvuOYT7hIbGcc2pXhDgXJwP5nY2Zf4srxbe+KyXUu9J6kvXMLqXtjl5N3Y2dv+no6ATyoKaeXWha/q6k/84oq9y/dl8056rSSs+/slsSTV3/afujkUSOdA6/Gd/e3nuk8csukX9wm465dVW9sXd/Uvfq1uDgVylbyAdg4kz1m3c/GTuY1jbdem+hNvlxf7mrqVWbFtCjYd3rUtOVnecOwM/7Mx4O8HX7h78Hb2tT/U2Zecds0dy7musoA6/956/Kqtbee48z/bcSz8olZvW6JzZ/I1ujnArqlTp8YbTmuo1yoMaaiPdGkRRsRPjR9fXx+pmR8mqBThONbAOGZRQ33DzZMmTeKyM0NOPfXU4xumNvxGq0BlisVi343H4x0S7nfvv6iTYUBzc3MgffJG6SP3M7F8ac4AeZ68yf28rfRNi/TNep2MMpO++I70yyJ5rrRLfE0nwwDpj/vleXOCPD45e/bso3Qyyqipqek/5PmyR/qlWfrlBp0MVBY5eZfJSXyuPL4jEomcKOX/lfJqnY0yaWhoeJf0wz5Xln75pLvWSfom4JOM8pJE6RPSLzfW1dUdJ+Xp0idvkvpunY0ykb5ok374ulbduPZVCf6DYYAbtyZPnvwUrbr6wxIZf74bxSfPlw/J8+MvWnV190HJHVoFKoOctP2SIEW0/CuJj2v5NIl7XRmlJwPKDySu1Kp7xzz8M37SL0/MmTPnGK2ihOTYr5Z+CX8sQp42r5H6ra4sbzie19jYyE8tlon0wxaJ8NfO5PEb0kffcWVJlD4g9SdcGaXnElU3dg298Za+eKS5ufloLe+Rfoq5MkpLjv2FEhdp+dUS/3DlqVOnPsP958+VgYojJ7K8Dje+S6swRPrmt1qEEe4FWvqFf1kb4xJY6ZswiYUt8voynMTChvr6+tfK8yVMYgEAAAAApRRLu5wAtqRfTgAb0i8ngB3SJ+5ygm9rFYZIvzxWV1d3pFZhgPTJS+U5069VoHKRxNpFEmsPSaxNmsRyOYFB0i9PkMTaoknsNq0CAAAAAEpG3pE1RCKRt2kVhsg75fO0CCPq6+ufLc+Xz2kVRrS0tBzqQqswRPrlCC3Cjolz5sw5XMtA5ZJEicsJjOJyAnu4nMAm6RMuJzCKywns4XICVA15UX7/1KlT36RVGNLQ0PBlLcIId09F6ZfZWoUR8oL8JXlhPlerMET65W4+jbVF+uPF0i+btQoAAAAAKJkYlxOYxeUE9nA5gU3R/T8L/DutwpB4PB6cdNJJXH9piIxjL5Dny+1aBSoXSaxd/BSgPSSxNkmffEwS2Qu0CkOkbwK+RGSLS2Ll+UISCwAAAAAlJ++SZzc0NEzWKgyRd8pLtAgj4vH48fKc4dZnxrgv3Lm+0SoMiUQiJ8rDxP01WDBp0qTDZBx7tVaByiUnMpcTGMU1sfZwOYFN0idcTmCU9A2XExjD5QSoGg0NDf8h8TKtwhAZZJq0CCNaWlqOlReAk7UKI+L7fUWrMESS2A3ukz+twgD3oy3SL51aBQAAAACUjLwb43ICo7icwB4uJ7Apyi22zIrH41xOYIx+EvuAVoHK1djY+CsJkliDWlpaSGKNkefKa+VFmSTWGHlB5ppYo6RvSGKNcUmsPF9IYgEAAACg5CKRyOflnXKjVmGI9MtNWoQR+q3epVqFEfX19S9ubGx8r1ZhiIxjZ8gDt9gyxH0yLs+XmVoFKpcMMFwTaxTXxNrj7uQhSeyAVmGEvLlolnGMNxcGuWtiW1paDtUqDKirqztOni+PaxWoXM3NzS+Uk/lZWoUhksT+pxZhhLwYHyHPl9dpFUa454r0yxytwhBJYi+YO3fuIVqFAbNnzz5K3oz/WqsAAAAAgJKJcTmBWVxOYA+XE9gUj8dbZBxbplUY0tjYyOUExujlBE9oFahcMsBwiy2jpk+fThJrjDxXXi5vLkhijeGaWLu4JtYerokFAAAAgHKJRqP/K+/IZmsVhki/3KNFGCHPlxdJbNQqjIjH42+SOFurMETGsV9pEUZMmjTpMOmXX2oVqFxugJHgcgKDuCbWHq6JtYnLCexy18TKA/eJNaSuru5I7Regsk2ePPkp8q7sKK3CEPfTgFqEEe5WQVOnTn2GVmFEc3Pzy+QNxmStwhB50/c/WoQR7hpledPHLekAAAAAoOS4nMAuLiewh8sJbOJyAru4nMAeLidA1ZATmVtsGdXS0sIgY4xLYuPxOEmsMSSxdpHE2kMSi7IIdnYGwS2LKib23dr2Am16VQv6V3r332T8Y0nNDFz7Nnc87D0GFmNHqmb6peLGsZuSL9SmVzV5vrT69t9k1NI4dsuih7zHwGjIefQ1bTowEkmsTSSxNpHE2kQSaxNJrE0ksagaJLE2kcTaRBJrE0msTSSxNpHEomqQxNpEEmsTSaxNJLE2kcTaRBKLqkESaxNJrE0ksTaRxNpEEmsTSSyqBkmsTSSxNpHE2kQSaxNJrE0ksagaJLE2kcTaRBJrE0msTSSxNpHEVqCZM2cGTU1NK7RqTjQa/Yq7h2dzc/PROqkkSGJtIom1iSTWJpJYm0hibSKJrUDTpk0LYrHYpVo1JxKJfC4ejwezZ88+SieVBEmsTSSxNpHE2kQSaxNJrE0ksRWIJNaPJNYmklibSGJtIom1iSTWJpLYCnSwJFYSyPc2Njbe3tzc7C45cP/SD9zyMv0P9fX1x+hiI8hy75Ht7dZLAMKYPn16IIloRBc5wKxZs46LRqM70v+OS1yl/HqS2PEFSazBIIm1GSSxZoMk1mCQxJoNkljhS2KlXu+SSUke/6STRpD5r5Bw612ik0INDQ3/Iev9h1ZHkCR1t0tOtTpMtnGXzNspSe8ROmmYTG9yCSxJ7NhBEmswSGJtBkms2SCJNRgksWaDJFaMTmLr6+uf7ZLNSCTyc53k5RJZl+jK46d0ktecOXMOP/XUU4+XhPR8t7wkq8/XWW4bfb7ENp0scxFJ7NhBEmswSGJtBkms2SCJNRgksWaDJFaMTmKlfJpLLBsaGj6gkzJyyaUsv0Cr7pPTNzY2Nj4k0x+S6T2SCJ8nj9Nk+tNl2if0MoHjdXH3tx6Wed5Pe4fI/M+SxI4dJLEGgyTWZpDEmg2SWINBEms2SGLF6CR28uTJT3HXs8q0dp3kJfNPcUmpJJmnurokrP/p6pLEvj9cYBRJRK/QSxTSk9jbZPmDPkFk+9tIYscOkliDQRJrM0hizQZJrMEgiTUbJLHCd02sJJYv14RzpySRL9LJw2TaPJewukRWJ01w17TqOit1Uqiuru5IWW6zxPrRSawj9btk3j5Jgl+jk0Ky/RfK9Hvkb60hiR07SGINBkmszSCJNRsksQaDJNZskMQKSRTdNaf/o9UDyPzPSyK5UuJvEpdJ/TxJMJ+jsw8g80+RWCzL3iyPq+VxipvuLk+Q+h9OPvnkp4ULjiJt+LHMv17iBklok1J/k5vu1pPy+e7a2nDBEiGJtYkk1iaSWJtIYm0iibWJJBZVgyTWJpJYm0hibSKJtYkk1iaSWFQNklibSGJtIom1iSTWJpJYm0hiUTVIYm0iibWJJNYmklibSGJtIolF1SCJtYkk1iaSWJtIYm0iibWJJBZVI7j9miDYIi8AFRL7bl1TG0nsziu8+28yetfUzuD/z9TD3mNgMfZcXTtJbKWNY/9cWRtJ7D87W337bzJqahzrfMh7DIzGvts6SWLhF5w/IQjOq5zY96MJtZHE/tq//ybjZxNqZ/D/yYSHvcfAYvy2dvql4saxn06ojST2JxNafftvMmprHHvIewyMhjxfSGLhRxJrE0msTSSxNpHE2kQSaxNJLKoGSaxNJLE2kcTaRBJrE0msTSSxqBoksTaRxNpEEmsTSaxNJLE2kcSiapDE2kQSaxNJrE0ksTaRxNpEEouqQRJrE0msTSSxNpHE2kQSaxNJLKoGSaxNJLE2kcTaRBJrE0msTSSxqBoksTaRxNpEEmsTSaxNJLE2kcRWgFgsdlpLS8vztYoMSGJtIom1iSTWJpJYm0hibSKJNS4ajb6zqakpaGxsfIlOQgYksTaRxNpEEmsTSaxNJLE2kcQaJcnrZ2Ox2OPy+IQ8Bq6ssU+mfUUXC7W0tBwaj8f/IfOelEe37FB8WBcZwSXFbhuy3rGyzIMS+3R593ihLuY+AZ7tpuk23Ty3/Vk6ewSd//+0vFm2P9wW3YePhQsWEUmsTSSxNpHE2kQSaxNJrE0kscZJAnjQT2Jl/kaJe7U6giSRP25ubg7k8bk6KeSmyfZcgjlJJw2TaTe5xFMT0Ffo5GEy7W6JR7Q6zC0v7XDzPqqTRpD5K912Z8yYUbTEjSTWJpJYm0hibSKJtYkk1iaSWOMOlsTKvD+5ZFSrEz3hlnlUYp4rD3FJrCSUF2l1hIaGhre7bUpM10kjyLZ+7Noj23imTgq5JFbix1r1kr/pPkku2pOLJNYmklibSGJtIom1iSTWJpJY48ZIYv8psVcSwy/J47mZIhKJnKmrhDSJ9R5I93f0coN36qQRZL1vZEpi5e+8Tatess3HSGL/HSSxBoMk1maQxJoNkliDQRJrNmo2iZXHl+qkYS4RdfPq6uqO1EnjUsQkdqFWvWRdd93sIq0WHEmsTSSxNpHE2kQSaxNJrE0kscZJcniCSzolqbxAJ02YNGnSYVp0ieFC9+9/mf+VIAjCSwjUIZLcHifzdmp9WLGSWIlNst4D7gtjOnnC3LlzD5F1Pi7h/uY1OrkoSGJtIom1iSTWJpJYm0hibSKJrRAu6ZQE0X3rv3Pq1KkHDBoy/9USG2T+Lnm8UuK79fX1z9bZI8gyX4hEIm/R6ggy/akSn5OE9HidNIJs861u/uhPf/WT2PByAkmE3yt/f53EoMRil4iHCxUZSaxNJLE2kcTaRBJrE0msTSSxKIj0JLZcSGJtIom1iSTWJpJYm0hibSKJRUGQxGYfJLEGgyTWZpDEmg2SWINBEms2SGKREUmsTSSxNpHE2kQSaxNJrE0ksagaJLE2kcTaRBJrE0msTSSxNpHEomoEf5CT5JeVE/t+XSNJ7O/8+28yJOHWZle9fb+QJNZ3DCzG72soia20caxWkthfShLr2X+TUUvj2C8lifUdA6Mh7SWJBQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIBRTj/99GdHo9H3aTUrsVhsmcQmid/KNs4fCqn/UhdBjk4++eSnybH8oFbzUl9f/2zpk0C295hOQo4ikchTJc7R6ri5PpgxY0Yg/fCthoaGeumLWDweX97c3Oz65Z26GHJ0xhlnPEWOY5NWx831p/TDXY2NjX+V9WdKNEh8samp6TGZfrUuhjzJOf969xzQalakH06Q+Lsbw6S/ztTJKIE5c+YcLsd9mlYBe+QE/avEr7SaFRns18vgwqBSBNInm+X4XqzVnEn/RGRbj0rMle2RxOZJjmeHHMe7tJo36ZdTJGrmhuzFIn3yTYmbtVoQsr0B6ZtvaBV5kON4v8TrtDoukrC+Tdb5vBQnurp7npDElpYc89PkeXC7VgE75OScIydnSh7d4LJNokuiR6a9SBcZkyw/KMvn9Cku/GSQ/rrrCzmuD8jjTolOKXc3NDQ8TxcZN1n3HxLzXVm28b8SJLE5kuNYL+GeI7vdcXRl1y+S1L5dF8mJbGeLxCVaRZbkefEu1w8St8lxvF8eU64uz6NmXSRnsr1HZFuMb3mQ49cqx3G1xOPyXLlaHsPXmbq6uiN1kXGT9UhiS2TKlCnPd88jOeab5PFRifB5JXGuLgLYICdpzp/EynqnS0Ql6mWAOre5ufl+eXzEvYPWRZAjOaY5fxIr/fDCxsbGoKWl5Wk6iSS2QPL5JFb69HUzZ84Mpk+f7vrGXUawfurUqS/X2ciDHMuCfRIrz52PTJs2zfXPm3US8iTnftafxI4m65PElpgccz6JhW1yknqTWDlxvyPTvzYq3q2zD0pe6HkByJMca28SK9M/n9YfYcjxjuts1293SszT6jBZ7lsynSQ2T5mSWJn27dH9IvFRnZ2RLPP/NKF9o05CDuT4eZNY6a8zR/XJ11ySqrOHSR8cKuv/U+b9TRKlp+pkFIgcd28SK8f83PS+cSFvwp+js0eQeSSxJSbHnCQWtslJmvMnsZnISf9QU1PTaVpFDqRPNktcpNVxqaurO0HWebcvpE8ulsfHXVleqN+lqyBLmZLYfLhPzWWb52sVOZDjl/MnsfKceEDW/bZWUQRyjPkktgLJMSeJhW3yAvoTOUn3anXC7Nmzj9LiQcnJPUfidK2G5AX+HJn2hDz+t05CjuQ4/lzeCASTJk0K+2Pu3LmHhDNyJH3M5QQFIMewSfrmca1O+PCHPzyuT+1kvQvcc0arIXnunSrTHpbI6s0KDiTHMOqeLzL2HO/q473mUtZbJX2zRvri5VJ+tSfySrywn/TLgBzny7Sa03gmfUESW2LueeHeZEv/neDq9fX1x4QzAEvcbTTchdwtLS3H6qR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AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAycYcP+PxycwqWv7GAZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('../images/one_step_multivariate.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from keras.models import Model, Sequential\n",
    "from keras.layers import GRU, Dense\n",
    "from keras.callbacks import EarlyStopping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "LATENT_DIM = 5\n",
    "BATCH_SIZE = 32\n",
    "EPOCHS = 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Sequential()\n",
    "model.add(GRU(LATENT_DIM, input_shape=(T, 2)))\n",
    "model.add(Dense(HORIZON))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer='RMSprop', loss='mse')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "gru_1 (GRU)                  (None, 5)                 120       \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1)                 6         \n",
      "=================================================================\n",
      "Total params: 126\n",
      "Trainable params: 126\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 23370 samples, validate on 1463 samples\n",
      "Epoch 1/50\n",
      "23370/23370 [==============================] - 3s 126us/step - loss: 0.0119 - val_loss: 0.0023\n",
      "Epoch 2/50\n",
      "23370/23370 [==============================] - 3s 125us/step - loss: 0.0013 - val_loss: 0.0014\n",
      "Epoch 3/50\n",
      "23370/23370 [==============================] - 3s 111us/step - loss: 8.1630e-04 - val_loss: 6.3127e-04\n",
      "Epoch 4/50\n",
      "23370/23370 [==============================] - 2s 82us/step - loss: 6.9678e-04 - val_loss: 5.6645e-04\n",
      "Epoch 5/50\n",
      "23370/23370 [==============================] - 2s 82us/step - loss: 6.2508e-04 - val_loss: 5.0461e-04\n",
      "Epoch 6/50\n",
      "23370/23370 [==============================] - 2s 79us/step - loss: 5.6529e-04 - val_loss: 5.9147e-04\n",
      "Epoch 7/50\n",
      "23370/23370 [==============================] - 2s 83us/step - loss: 5.3266e-04 - val_loss: 5.6215e-04\n",
      "Epoch 8/50\n",
      "23370/23370 [==============================] - 2s 96us/step - loss: 5.2366e-04 - val_loss: 6.0317e-04\n",
      "Epoch 9/50\n",
      "23370/23370 [==============================] - 3s 121us/step - loss: 5.1777e-04 - val_loss: 4.9150e-04\n",
      "Epoch 10/50\n",
      "23370/23370 [==============================] - 2s 101us/step - loss: 5.1019e-04 - val_loss: 4.4721e-04\n",
      "Epoch 11/50\n",
      "23370/23370 [==============================] - 3s 138us/step - loss: 5.0375e-04 - val_loss: 4.3965e-04\n",
      "Epoch 12/50\n",
      "23370/23370 [==============================] - 3s 141us/step - loss: 4.9972e-04 - val_loss: 6.6251e-04\n",
      "Epoch 13/50\n",
      "23370/23370 [==============================] - 2s 100us/step - loss: 4.9571e-04 - val_loss: 7.1562e-04\n",
      "Epoch 14/50\n",
      "23370/23370 [==============================] - 2s 91us/step - loss: 4.9014e-04 - val_loss: 6.0718e-04\n",
      "Epoch 15/50\n",
      "23370/23370 [==============================] - 2s 87us/step - loss: 4.8524e-04 - val_loss: 4.1987e-04\n",
      "Epoch 16/50\n",
      "23370/23370 [==============================] - 2s 86us/step - loss: 4.8055e-04 - val_loss: 5.5782e-04\n",
      "Epoch 17/50\n",
      "23370/23370 [==============================] - 2s 103us/step - loss: 4.7836e-04 - val_loss: 4.1921e-04\n",
      "Epoch 18/50\n",
      "23370/23370 [==============================] - 2s 95us/step - loss: 4.7221e-04 - val_loss: 4.8043e-04\n",
      "Epoch 19/50\n",
      "23370/23370 [==============================] - 2s 82us/step - loss: 4.6826e-04 - val_loss: 5.5102e-04\n",
      "Epoch 20/50\n",
      "23370/23370 [==============================] - 2s 81us/step - loss: 4.6583e-04 - val_loss: 5.0874e-04\n",
      "Epoch 21/50\n",
      "23370/23370 [==============================] - 2s 81us/step - loss: 4.6402e-04 - val_loss: 4.0455e-04\n",
      "Epoch 22/50\n",
      "23370/23370 [==============================] - 2s 89us/step - loss: 4.6187e-04 - val_loss: 4.0777e-04\n",
      "Epoch 23/50\n",
      "23370/23370 [==============================] - 2s 86us/step - loss: 4.5687e-04 - val_loss: 3.9960e-04\n",
      "Epoch 24/50\n",
      "23370/23370 [==============================] - 2s 94us/step - loss: 4.5838e-04 - val_loss: 5.3422e-04\n",
      "Epoch 25/50\n",
      "23370/23370 [==============================] - 2s 88us/step - loss: 4.5560e-04 - val_loss: 5.5244e-04\n",
      "Epoch 26/50\n",
      "23370/23370 [==============================] - 2s 94us/step - loss: 4.5583e-04 - val_loss: 4.8834e-04\n",
      "Epoch 27/50\n",
      "23370/23370 [==============================] - 2s 100us/step - loss: 4.5467e-04 - val_loss: 3.8960e-04\n",
      "Epoch 28/50\n",
      "23370/23370 [==============================] - 4s 173us/step - loss: 4.5116e-04 - val_loss: 4.4075e-04\n",
      "Epoch 29/50\n",
      "23370/23370 [==============================] - 3s 149us/step - loss: 4.5101e-04 - val_loss: 3.8978e-04\n",
      "Epoch 30/50\n",
      "23370/23370 [==============================] - 4s 156us/step - loss: 4.4988e-04 - val_loss: 3.8001e-04\n",
      "Epoch 31/50\n",
      "23370/23370 [==============================] - 2s 98us/step - loss: 4.4913e-04 - val_loss: 3.8835e-04\n",
      "Epoch 32/50\n",
      "23370/23370 [==============================] - 2s 100us/step - loss: 4.4764e-04 - val_loss: 4.7772e-04\n",
      "Epoch 33/50\n",
      "23370/23370 [==============================] - 2s 102us/step - loss: 4.4633e-04 - val_loss: 4.0662e-04\n",
      "Epoch 34/50\n",
      "23370/23370 [==============================] - 3s 127us/step - loss: 4.4495e-04 - val_loss: 3.7043e-04\n",
      "Epoch 35/50\n",
      "23370/23370 [==============================] - 3s 108us/step - loss: 4.4359e-04 - val_loss: 3.9966e-04\n",
      "Epoch 36/50\n",
      "23370/23370 [==============================] - 3s 139us/step - loss: 4.4439e-04 - val_loss: 5.9449e-04\n",
      "Epoch 37/50\n",
      "23370/23370 [==============================] - 2s 103us/step - loss: 4.4372e-04 - val_loss: 3.8925e-04\n",
      "Epoch 38/50\n",
      "23370/23370 [==============================] - 2s 105us/step - loss: 4.4062e-04 - val_loss: 4.7812e-04\n",
      "Epoch 39/50\n",
      "23370/23370 [==============================] - 2s 95us/step - loss: 4.4057e-04 - val_loss: 4.2858e-04\n"
     ]
    }
   ],
   "source": [
    "earlystop = EarlyStopping(monitor='val_loss', min_delta=0, patience=5)\n",
    "history = model.fit(train_inputs['X'],\n",
    "                    train_inputs['target'],\n",
    "                    batch_size=BATCH_SIZE,\n",
    "                    epochs=EPOCHS,\n",
    "                    validation_data=(valid_inputs['X'], valid_inputs['target']),\n",
    "                    callbacks=[earlystop],\n",
    "                    verbose=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluate the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "look_back_dt = dt.datetime.strptime(test_start_dt, '%Y-%m-%d %H:%M:%S') - dt.timedelta(hours=T-1)\n",
    "test = energy.copy()[test_start_dt:][['load', 'temp']]\n",
    "test[['load', 'temp']] = X_scaler.transform(test)\n",
    "test_inputs = TimeSeriesTensor(test, 'load', HORIZON, tensor_structure)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions = model.predict(test_inputs['X'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>h</th>\n",
       "      <th>prediction</th>\n",
       "      <th>actual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-11-01 05:00:00</td>\n",
       "      <td>t+1</td>\n",
       "      <td>2,737.52</td>\n",
       "      <td>2,714.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-11-01 06:00:00</td>\n",
       "      <td>t+1</td>\n",
       "      <td>2,975.03</td>\n",
       "      <td>2,970.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-11-01 07:00:00</td>\n",
       "      <td>t+1</td>\n",
       "      <td>3,204.60</td>\n",
       "      <td>3,189.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-11-01 08:00:00</td>\n",
       "      <td>t+1</td>\n",
       "      <td>3,326.30</td>\n",
       "      <td>3,356.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-11-01 09:00:00</td>\n",
       "      <td>t+1</td>\n",
       "      <td>3,493.52</td>\n",
       "      <td>3,436.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            timestamp    h  prediction   actual\n",
       "0 2014-11-01 05:00:00  t+1    2,737.52 2,714.00\n",
       "1 2014-11-01 06:00:00  t+1    2,975.03 2,970.00\n",
       "2 2014-11-01 07:00:00  t+1    3,204.60 3,189.00\n",
       "3 2014-11-01 08:00:00  t+1    3,326.30 3,356.00\n",
       "4 2014-11-01 09:00:00  t+1    3,493.52 3,436.00"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eval_df = create_evaluation_df(predictions, test_inputs, HORIZON, y_scaler)\n",
    "eval_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.015356448361113459"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mape(eval_df['prediction'], eval_df['actual'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wVFDRGGi0tsJPfwrr1vm7Jcp4sUVjRwe0tfm3LYpXPPccFD3yJhw4ADfcICuzsmSpIaqO53BTH18r+CG1tdaKr35VsuA+/bRf2xWIqGhUFEUJQvr64Ne/ln7OsOGpoPMaA41//EOcjcpKdakCFVs0gs5rDAB6euBLX4Lr75wFGRnw+c/LhuxsWWqIquN5q2EJT5SdxpNPWisWL4bjjtMQ1XGgolFRFCUI2bcPvv99+Pd/N4eGp6rTGJg8/rgsOztVcAQqFRX9LpWeQ8dTXi6RqW82rmT7uf/Zn4FaRWPAUNg6G4Dnn3dbeeGFsH27hhePERWNiqIoQYjdH33hBYPnez+v4amBTmEhbN4Mq1fLe3fHSgkMmpvl34oV8l6T4TieoqL+17+ru6r/TUoKRERoeKrT6e2lsEsGad59FxoarPULFshy/37/tCtAUdGoKIoShNgPx/i4Xr7FfRyJntW/URPhBB5/+hOEhMDtt8t7FY2BR1WVLFeulKU6jY7HFo0Xz36fv2yIcp1CQkLEMVan0dm0tFBIHnGRnfT1Sf4bAPLyZFlY6LemBSIqGhVFUYIQWzTe9x8VlJPFXW+c0L9R5zQGFr29Mv/m7LP7nUa73p8SONhC33YaVTQ6nqJPe5hGB7/68sf09cH997tt1LIbzqe5mULyOH9FBamp8MIL1vp582SponFMqGhUFEUJQmzReNGKUr7O4/zmuXns2WNttNOPq9MYGLz+urhUV18tYXFhYeo0BiL2OTvmGJkbp6LR8RQVdJNDCfMWhnHxxfDQQ5LEGBCnUcNTHU37wRYqyGR+ZifnnguvvAJdXUBMDKSmqmgcIyoaFUVRgpCGBplyE91Wx6/4PrHRfdx8s5V0MywMoqNVNAYKjz8OSUlw/vkSFpeWpqIxELHd4fR0OZ8qGh1PURHMpQhmzuS735XgDDsfFdnZUFsL7e3+bKIyAsV7uwDIy+3l/PNlSvHmzdbGvDwVjWNERaOiKEoQUl8v/VLjUBMzqefnt7eyaZNbib/4eBWNgUBjoxSKu/JKmDZN1qWna3hqIFJZCbNmyXlMTlbR6HBME4oqwl2i8cQTYc0auOceiRh3ZVBVt9GxFH4qpYny5ht85jNy6blCVFU0jhkVjYqiKEFIQ4OIRhobAbjum9NYvRq++12p2MCMGTqnMRB4+mmJp7rmmv516enqNAYilZVy7kBEo2ZPdTQHD8KRjjCXaAS5fxYXw4YN9JdOUdHoWAqLpUTKvEXhREfDWWeJaDRNRDTW1or9qHiFikZFUZQgZIBojIwkJHo6t90mHaG9exHRqE6j83nsMcm2uXx5/7qMDBEgpum/diljp7JSzh2o0xgAFBfL0l00Xnwx5OTAb3+L1moMAArLp5FMHfHpMYBE+BcXQ0EB/RlUteyG16hoVBRFCUJcorGpyVWjcelS2bZrFyoaA4COD3eSn28OdBlB3KqODpeLrAQI7k7jzJkqGh2OXW4jN6QMEhIAyV90yy3w3nuws242hIeraHQwhdVR5FHoSv523nmy/oUX0LIb40BFo6IoShAywGm0RGNenvRxPvkEndMYADzxu3qOJZ+P8748cIMtPHReY+Bw5IgM4LiHpzY0QF+ff9uleKSoCAz6yElqlgRUFp/7nCx37g4V51jDUx1L4cEZIhpjxGlMT4djj7VEo5bdGDMqGhVFUYIM0xSt6BKN1ih5RAQsWODmNOqcRkdTWC6Jb+55KmngBjvEUec1Bg72uXIXjb29OnDjYIqKIG16I5Gz4gasz8kBw7CcSK3V6Fja2qCqZQZ5EeUDRP/558P770N9W5RkolbR6DUqGhVFUYKM5mbo6RnqNIKUiNPw1MCgrC4KgL/+LYQDB9w22MJDRWPgMJxoBE2G42CKimBueIVrPqNNZKRoDRWNzsaeqpgXXT1g/fnni8H/0ktoBtUxoqJRURQlyGhokOXgOY0gorGsDJqnzZSsnB0d/mmkMirlTbHkhZfQ0wMPPui2ISVFJldpeGrgYItG90Q4oPMaHUxREcw1ioaIRoC5cy3RmJUFBw5YKakVJ+ESjfEDB2aOPRbmzHGb16ii0WtUNCqKogQZA0SjW3gq9CfD2dOeIy/UbXQsZa2JnDpjB+efL6LRpe9DQ6XXo05j4GCfq7Q0WdpCREWjI2ltlWoMc7v2jiwa7Qyq5eVT2j5ldGwtOC+pacB6w4Bzz4VXX4W+uXlyDepUDa9Q0agoihJkuERjXLck4BjkNALsarI6r/qwdCSdnVDTmUjmjGZuvVX6NevWue1gl91QAoPKSnEXIyPlvTqNjsZVbqP9k2FF47x5IipbZ+XKCg1RdRyFhTArvJG4xLAh21avhpYWKJ2xvH9nZVRUNCqKogQZLtEYZrmIbqIxOxuiomBX3SxZoU6jI7EjT7OSj3D66bBsGdxzj1tpxvR0FY2BREVF/3xGUNHocGzRmEuxR6cRoBhLNGoGVcdRWAh5YaWuchvuLFkiy929C/p3VkZFRaOiKEqQYYvG5BCrjp9beGpIiDwwd1VZ61Q0OhI72i0ztRPDgNtukwRGb75p7ZCeLkLEpSIVR+NeoxFk5CYyUhPhOBS7RuNcPM9pBNjfYs0vVqfRcRQWQp5ROLJobJwj8aoqGr1CRaOiKEqQ0dAgz8GEHqtD6uY0gpVBtVTqVqlodCZlJVK/LytdlpddBrNmidsISHhqe7skOlIcy89+JvOn2ioaBopGwxC3UZ1GR1JUBPEx3STSNKJoLCq1ajWqaHQUra2SnyivZ++wojEuTk7brn3h8kJFo1eoaFQUxTtME/72N822GQA0NEB8PIQ2W4JiGNFY2xBOHck6p9GhlO/vxKCP9KxQQEypG2+Ef/7T6t9o2Y2AYONGSe3/pcYH6Z6TNXDjzJkqGh1KURHMndUib4YRjfHxclt1ZVDV8FRH4cqc2rVrWNEI4jbu3o1kULUPUEZERaOiKN7x4Ydid2zY4O+WKKPQ0OCWORWGFY0AuzhGnUaHUra/h9kcIGJWvGvdDTdARATcey/9olHLbjia+npISujlRc7jG698kb4+t43qNDqWoiKYG2/F+Q8jGmFQBlV1Gh2FbRzmMXx4KshzsKAAeufOV6fRS1Q0KoriHfn5stQ5OI5niGh0m9MI/WU3drFURaNDKSs1yaR8gOBPTYULLrDGbdRpDAjq6+GCEw7yU+7gyffm8r3vuU1DVdHoSHp6xDicG1UjK5KSht1vgGisqpK6t4ojcJXbYP+ITmNnJxQlHifPSvt5qXhERaOiKN6xfbss9cbqeAaIRsOAGTMGbE9NFS2yK2KlikaHUl4dShZlQ1ziU04RnVjZO1sScKhodCymKddickgj/8nP+NZVTdx9N/zyl9YOyck6COdAystFOM4Ns66/sKElG0BEY3k5dKdly8nWa9Ex7N8PqcndxHBkyPPPxo642Y31Qt3GUVHRqCiKd6hoDBhcorGpSVzGkIG3esOwkuGo0+hI+vqg/GDkEKcRYM0aWX6wNRRmz9bwVAfT1iZTwJN6D2IA9zwwjcsvhx/9CJ57DhGNhw9Dd7e/m6q44cqcau73GJoKUquxtxfKpi+UFRqi6hgKCyEvvV3eeHAaFy2S5a4jOf0HKSOiolFRlNHp7YWdO+W1ikbHM8BpHBSaanPMMbCrZwFmkybCcRoHD0JXj+U0DgqNW7ECpk2DLVvQWo0Ox1X6prMKEhMJiYniT38SHfL88/QLEntHxRHYojG3Y8+IotGVQbU3W16oaHQMhYWQl9IsbzyIxuhoyMmB3TWJMrCqonFUVDQqijI6hYWS3h9UNDqcri5JN+4SjYOcKptjjoHmvlgqD0ZMbQOVUbETMWZRNkT0R0TAsceqaAwE7OmKyUfKXHNQIyJkTvGePYjT6L6j4giKi+U8pTUXeCUa9x+eKaJDM6g6guZmqK2FvCQre7gH0QjyHNxdEAqZmSoavUBFo6Ioo7NjhyyTk7UunMOxTQtXeOoIohFg18FZU9MwxWvKy2WZGdUA4eFDtq9ZA1u3IiUcKivdMqsoTsLWgkmHigbUaFy8WESjmaSi0YkUFYkDFVpfO6JonD0bpk+3ajWmpanT6BBc5TZmHJQXI4jGJUtg3z7onrtQRaMXTJloNAzjKcMwDhiG0WwYxqeGYVxrrb/SMIxWt39thmGYhmGssrb/2DCM7kH75Lp97grDMLZZx20zDGPFVH0nRTlq2L5dOq9r16rT6HAGiMYRnMYlS2S561D6sNsV/+FyGpNah92+Zo3MldsZsgKOHNFamw7FFZ5av3eIaGxpgareVFmhyXAcRVERzM21shiNIBoNA3JzteyG03CV24iulhejiMbubiiceZIcqANwIzKVTuPPgWzTNOOAC4C7DMNYZZrmOtM0Y+x/wE1AMfCx27F/c9/HNM1iAMMwIoANwFNAAvBnYIO1XlEUX7F9u/R0UlNVNDqcIaLRw5zGxESYE32IT1pzpq5xileUl0Nc2BFmJA91GaE/Gc6W5sXyQkNUHYnLaWwqHCIaAfbUzxq4o+J3TNMSjWkdkpFqBNEIbmU3srJUNDoEWzTOjbCShMXGetzXFXETcawkpdJrcUSmTDSaprnbNM1O+631b+4wu34NeMI0vZL7pwNhwD2maXaapvl7wADO9EGTFUWx2b5dMnAkJIgQ0dE4x+LqqCb0jRieCrB01kF2deXp+XQYZWWQFXHA47nLyJDQuC1VGbJCRaMjqa8HwzBJoGl40Vgd37+j4gjq6mRO+NyZVlZpL0RjcTGYmVlSq7G3dwpaqYxEYSHMmQPRHQ2S7SY01OO+CxfKdNTd3Xn9BysemdI5jYZhPGAYRhuwFzgAvDRoexZwKvDEoEPPNwyj0TCM3YZh3Oi2fgmwc5DA3GmtH/y3rzcMY6thGFvrNBREUbynthZqakQ0JiZKAavW4cPmFP/jchqntcpI+Qii8Zj0Q+xhMb0tbVPUOsUbyssh06j0eO4MQ9zGLfss0aFlNxxJQwMkxPYQRq8ofYuZM2V6+J59oVJDTkWjY3CV24izzokXorG9HQ7E5IlgPHhwkluojEZhIeTlIRlxRghNBYiMlHO4u3F2/8GKR6ZUNJqmeRMQC5wCPAt0Dtrlq8Bm0zRL3Nb9HVgEzASuA/7LMIzLrW0xwOAiY4etvzH4bz9smuZxpmkeN3OUm4CiKG7YSXCWL+/vxGoyHMfiEo1YLzyEpwIck3OETiIp2qGDAE6irAyy+opHFPxr1sD+0nDqjZnqNDqU+npIirKyTqcPnDtsJ8MhOVlFo4NwlduItObDjdJfnDfPOs6wXui16HeKiqzz4oVoBKv8VEmMOJIqGkdkyrOnmqbZa5rmO0A6cOOgzV9F5iW677/HNM1q67j3gHuBS63NrcDgX0Qc0OL7livKUcr27bJ0F406r9GxNDTI6GnU4QOyIjXV477HzO8CYNfHXVPRNMULWlpkTCazs3BU0QiwJeEc7ag6lIYGSI6wuiNpaQO2DcigqqLRMdiiMSfEykblhdMIUNRpDQrotehXenokxDgtDRGNM2aMesySJbC/yKAjc76KxlHwZ8mNMNzmNBqGsRaYA/zfKMeZyLxFgN3AMsMwDLfty6z1iqL4gu3bpYZRYqKKxgCgocFKgnPAEo1z5njcd9FiA4M+du2amrYpo2OX28jqKxlRNK5aJQPjWyJP146qQ6mvh+SQRum4DkrGsXixDA7Uxs7T7KkOorhYBMf0wzWywq6l6YGsLLkO9x+y9quqmuQWKiNRVydT9FNT8dppXLJEIov3zT5dReMoTIloNAxjlmEYlxmGEWMYRqhhGP8GXA686bbb14BnTNNsGXTshYZhJBjCauDbSMZUgE1AL/BtwzCmGYbxTWu9++cqijIR7CQ4oKIxAHCJxmorvGr2bI/7RqfGkksxu/aFTU3jlFFx1WikfETRGB0Ny5bBlu5VOqfRodTXQ1Jf3bADN65kOGHL1Gl0EBUVIgSpqxPBMW3aiPuHh8uYatGBKIiI0AEcP1Njaf2UFMYUngqwO+YELbsxClPlNJpIKGol0AT8BrjVNM0NAIZhRAJfYlBoqsVlwH4k5PQJ4Jemaf4ZwDTNLuAiJKz1EHANcJG1XlGUidLWJpVvbdFoz49T0eivBlS7AAAgAElEQVRYBjiNYWHWGw/MmMFC9rKvbPqUtU8ZGVeNRspGFI0AJ54IHx6eT295lXZ0HEhDAySbdcOeR5do7M5T0eggKiqs6ad1daOGptrMnQtFxYZYlCoa/UptrSxTUpASGl6Ixvnz5VG5m8WS5M/+EGUIUyIaTdOsM03zNNM0403TjDNNc6lpmo+4be+wtv1rmGMvN00zyarPuNAqq+G+Pd80zVWmaU43TfNY0zTzp+I7KcpRwa5dkoFz+XJ5r06j4xkgGlNTJZ+4J2bMIIcSSg9OV83hEMrLISy0j1RqRhWNa9ZAS1ckBW2ZMqquOIa2NsmqmdxbO+y8qtRUiI+HPW1ZsmObZjD2N6Ypmi8jg7GLxiJENGp4ql8ZIBq9dBojIkQ47mrOlBUaouoRf85pVBTF6diZU22ncfp0CdfR7KmOZUB46gjzGQGXaGzumKan1CGUlUFGUhuh9I3sEuOWDIc1GqLqMFxZjLtrhhWNhmElw7FT/avb6HcaG6GjY3xOY2MjHJo1X51GP2OLxtQU02vRCDKvcXe1NUinotEjKhoVRfHM9u1y083OlveGIe6HOo2OpK9PTo3LaRxhPiMA0dFkh8gkutLSSW+e4gXl5ZAVb1WSGsVpnDcPEuO6RTRqZ9VR2BowubPKYwbHxYthT611jjUZjt+xx13GIxoBiqKWynWoYRt+o6YGoqIgxjgi52EMorG4Ioy20FgVjSOgolFRFM9s3y6hqe4hjioaHcvhwyIcvRaNhkFOjPRuVTQ6g7IyyIwevcYmyBjOmlUqGp2ILRqT2ipGFI11h6dRT5I6jQ7AvoQy0k05H16KRletxpA8sSo1bMNv1Na6haaC16LxmGPANA0K0j4D+/dPXgMDHBWNiqIMy513mDy1bWF/aKpNQoKKRofiComb0SOdntHCU4Hs+EMAlJRMZssUb+jpkSlRWdNqZbg8MnLUY9acOo09LOZwfvEUtFDxFvtaTO45MKJoBChgkYpGB+ByGuOaobvba9GYmyvLoh5rTpwO4PiN8YrGJUtkuTt+rTqNI6CiUVGUIZgm3HtPH3d33tSfBMdGnUbH4hKNIdb5Gc1pBBISDWaEtarT6ACqqsQpzgytHDU01WbN2lBMQvjohZpJbp0yFlzhqdR77Li6MqiyWEWjA6islJqLqSEHZYWXojEmRoTK/uaU/g9S/EJtrVuNRvA4YDOYefMkIc6u8BXiNGqI8bCoaFSmjooKzfAXIDQ0QMuRUPJZSVPuqoEbVTQ6Fpdo7LXmR3khGklKIjusSp1GB+Aqt9FX6rVoXL1alh9VpFgpHBUnYGvABJo8dlzT0yEmxmQPS1Q0OoDKSgnOCG207p9eikawMqjWW4MDmkHVb9TUjM9pDAuDhQthd8dcOHJEpncoQ1DRqEwdJ58M3/mOv1uheEGxFelmEsLmhsUDNyYm6pwNh+IKieuqlhdehKdy9tnkdOyh9NPOyWuYP3nnHcjJkQmfDqdcchKR2bXfa9E4YwakJPdQTC68+OIktk4ZCw0NkBDXQxi9HkWjYcCiRQZ7wpdrIhwHMKBGI4xdNFZOk/n/6jT6hZ4eue7GIxoBFi2CgoZZ8kZDVIdFRaMyNdTWSo/ozTf93RLFC9wNi43vRgzcmJgoI3GdQSoyAhiX03jEUh/eOI2XX042ZZSUGsEZkbN9u2T5CYBOgO00Zrbt9Vo0AmTPDaM0arGKRgdRXw/JsdY9coQQucWLYY+5UJ1GBzCgRiOMSTTm5kJVlUHXrHQVjX6irk6iSlNS6B8kHKNoLK2dTjuRAfG88AcqGpWpYedOWZaUaOhGAGA7jWuSCtm0adBGuzOrbqPjaGiQge74w2XywptOT1oaOXlhtHVHUF8XhKrRHnEOgHCj8nI5ZdMPHRibaMyG0oj5sGkTtLZOWvsU72logKToDnkzimis7knhUE3HFLVMGQ7TFK03XqcxK0s+o2LmsdrH8ROuGo3ucxrHKBpN02Bf2DEqGj2golGZGmzRCPDuu/5rh+IVxUUmqRzg3EVF7NgxaAqjXQZA5zU6joYGOT0hNdXy5AwN9eq47LMXAFDy4p7JbJ5/sDsP1dX+bYcXlJVBVpYp19YYRWNZaxJ9Xd3wxhuT10DFa+rrIXn6EXkzimgEKKj2LmGHMjk0NkJ7u5tojIqSf16SlSXLshlL1Wn0E7ZoHBCeGhvr9fGuxFQzT1PR6AEVjcrU8MknciVHRaloDACKC3vIpZjTVxzGNOHtt9022p1ZFY2Oo6HBqtFYXe1daKpF9pfXAFD69w8nqWV+JMCcxsy0Xgn9HqNo7O4JoTpmQXCGqG7aBE884e9WjIn6ekiKaJE3XojGPfZcKsUvuGo02uGpY3AZwU00RsxX0egnaqwE0i7ROH06hId7fXxengToFMQcr6LRAyoalalh505YuRJOOEESUyiOprjIJJdiVp9gMH06bNzotlFFo2NxicYDB8YmGpfKaGzp5grJJhBMBIjTaJqW0zizXVaMUTQClB53Kbz0UvCli3/gAbjjDn+3Ykw0NEBy2OjzqrKyYHpYF3taMqXeiuIXbJ3nchrHKBozMiSxUZmRLfPpNEx8yhniNI4hNBVg2jRJaFTAQim7odfjEFQ0KpNPTw/s3g3LlkkG1e3boaXF361SPNDVBRU14eRSTERGCmvXMnBeo85pdCzjFY1xcZAY00XJkZnBF95o32sc7jQ2NkJbG2QmWO0dj2jM+6yI4+3bfd9Af9LW1p/lKQBoa5N/ySGNUsRvhDDx0FBYmNIkyXACIMNvsFJRIcvxisaICElWXdpl3Xd1XuOUU1srwWwxMYxLNII4/wWtGdDRoedwGFQ0KpPPp5+KElm2DNauldGbDz7wd6sUD5SWymTwXIph9mzOOEOMYldyP3UaHUtDAyQl9MHBg96V23AjZ34YpWF58NRTk9Q6PxEg4amu8Lho67pKSvL6WDs0rjTxWHnxz3/6sGUOwFZh7e3+bolXuLIYm/VeFRdfnNXGHhZrBlU/UlkpAn72bMYlGkGuw7KWxP4PVKaU2lpxGQ2DcYvGRYvg04PxdBOmIarDoKJRmXzsJDjLlsGJJ0rQuIaoOhY7c+pcimD2bE4/Xd675jXGxck5VNHoOBoaIGn6EQlPHIPTCJCdE0JJ9DGwfn1whVYFSHiq3bw54VbmxjE4jdOnS96j0voYWL06+OY1trXJMkDcRle91L6D3onGBT2Uk0VLYc0kt0zxRGWl3DJDQ8xxi8bsbCirj5E36lJNOTU1VmgqyH3fi2tvMIsWQU9vCEXMVdE4DCoalcln504IC4MFC0RwLFumotHB2KIxN6oWYmM5/ngJ+XDNawwJgfh4FY0Oo71d+tZJ9jyqMYrGnBwoa5+J2dYGGzZMQgv9hC0aa2uht9e/bRkBu4+ZFmI5omMQjWCV3SgFzj0XPvwwuIrF2w5jgDhxdjOTuw941XFddJKc632bnO2GBzMVFVYSnCNHJDRxnE5jRU0YvYSo0+gHbKcRmJDTCFAQvlxF4zCoaFQmn5075UqMsIrEn3wybNkSfAk3goTiYogM7SJ1jtwewsPllA2Z16ii0VH0h8RZL8YYnpqdDR1dodSkHQfr1vm2cf6kuVnizvr6HC2kbKcxtddSjxMRjaYJL7/sy+b5lwB1GpM6q70SjdnHyrmu2B4Y3y8YmUiNRpusLOjpMaiesVidRj9QW2vVaASZHzwO0bhwoSwLEk5S0TgMKhqVyWfnTnEXbdauldG8HTv81ybFI8XFkBNRTcicVNe6M86AXbvc+twqGh2Hq6PaY6WQG4fTCFB65jXw2msyLzIYaG6G3Fx5PVKI6vPP+9UdqKqCWbMgorle0vhNnz6m47OzpWRH77KV0nMKpnmNttMYIKLR5TS2lXslGtMzDAAqC9sms1n+5Qc/cOxv0jTFafSFaAQoS16lTuMU09Mj191EncbYWHGc90SsUNE4DCoalcmlqUnuxu6i8eSTZakhqo6kuBhyjZIBosOe1/jWW9aKxETNnuowBrgbhuH29PQOOwNnyZLzJIzzued820B/0NUloWYLFsh7T8lwOjrg4ovh17+eurYNoqoK0tKQwZjERCubg/dkZ0N3NxyoDYHPfx5efVVWBAO20xhg4amJrd6JxuRkmBbaTWWVEbxp/h94wLERDE1NMi7hqtEI457TCFAWs0RF4xRTVyfiPyUFeTFO0QgSGFfQPReKihw9pcEfqGhUJpdPPgGgPmsVJ54Id9+NDOdlZcG77/q3bcoQTFPuk3O7CgaIxlWrJI21a16jOo2OwyUaj5SLZRUWNqbjXWUbetIlnLO01Kft8wt2uY3RRGNpqXTWd++ekmYNR3W1FVFsi8Yx4jp/pcBnPyudpl27fNhCPxKA4anx8RDW3OhVx9UwID2xjYruVCgpmYIWTjF9fRJd5NB7ypAajTAu0ZiZKcvS8DwNT51iBtRobG8XsTdO0bh4MextSqGvq7u/FosCqGhUJptPPqGJeD7701PZssVtms3ateI0BlsR6gCnvl4SZ+b27BsgGofMa0xIUNHoMFyi8VDRmENTQZIdzZoFpWWGWB8B4uqMiJ0EZ/58WXoKT7U76nv2TH6bPDDEaRwjA0RjWpq8cfAcTq/p64POTnkdIL/J+npITjLFwfYyg2N6hkEl6a6B1qCivV2e9Q4VxENqNMK4RGNUlBxWZmaIiunq8l0jlRGxRWNqKv33/Qk4jW1d4VSQoSGqg1DRqEwqLVv3cU7Y6+z+NIzFi2HfPmvDySfLqL9DHyJHK67MqVaNRnfOOEP61LW1SKf20CEN3XAQLtHYWDgu0Qgyr7GkBOn5BEgHfUTszsPMmVL30JPTaP/wDxwYOez6tdfgrrt820YkitRVWnOcotHlcpQioh8CxpkbEffajAHyfRoaICneSvTmrWjMixLRaJeoCiaOHJFlba0ja226aqTa4akRETK5bRxkZ0NZhzU1wOFlfoKJAU6jD0QjILVT9++feOOCCBWNyqTR1gbnPXM1W3tX8re/GVx2mSRqaG+nf16jhqg6ipFE42mnyfLdd5FOrWlKhjLFETQ0yEh3ZG3ZmDOn2rgycCYnB4dL5d55mD3bs2h0H7wayW28/3748Y/7nS8fYTdrIk6jXauxpAQRyBAwImtE3EVGgAxk1NdDcqzlMnkrGrPDqCKdvh1B6DS6130tK/NfOzxQWSmVpFJT6a/ROMY5xTZZWVB2OF7eaIjqlFFjlTj1pWgsCFumTuMgVDQqk0JnJ1x8kcnmluU8+W/ruPji/gixwkJgyRJ5mGoyHEdhi8YcSoaIRntaWEkJ/Z1aDVF1DA0NkJRkytNznE5jdrb06XqTZgVMB31E7M5DbKwIaU8j/8XF/R2MkURjfr646wUFPm2mq0bjBEQjuIl++/hgOIdtbhlFA0QE19dDcowldr0VjenQRQR1+UGYQMV2GsGR8xorKuT2EBaGWxrV8ZGVBWV1UZigyXCmkNpaGTiLiWHCojE5WcYNCmJXq2gchIpGZVK46y547XWDP3Itl39RwnRs0bFvHzKsd9JJKhodRlERzI5rJYr2IcJjxgzpe5eX098p1QyqjqGhAZJm9MgcsAmEp3Z3w4GoucEhOMbiNK5dK1atp2Q49fX9nUAfhxDaWnZOUqeIpImKxrAwycQSICJrRGzRGB4eMN+noQGSIq12eykaMzJkWVnSPVBkBQPuTqMDp6S4ajSCtM+uPzQOsrKgozOEg8w6OkXjs8+OXiPWNPvjSX2EXaPRMOiPgPLy2huORYtgj7FEReMgVDQqk8KWLXDc3Cau4XFYuhSAvDzZNmBe45496lY5iOJiyI2tkzpxCQkDthmGzJsaIBr13DmGhgZIiuqQNxMITwUoCZkrHxjoc1YHi8aamqElDUzT+uHnWj0FD05jfn7/ax8nK3E5jVHWIMwERGN5uXXagiWZkR2empYWEN+nvV00X/I0K3PvGJxGgErS/JqQaVJwF40OdBpdorGnR0It7Lqu48BVdiNy4dEZnvqjH8Gll448F/C222SUZO9en/3Z2tpBNRph3E4jWGU32jIxi4rld6EAKhqVSaKgABZFl4vSWLIEgOhouU+4RONJJ8nyww/900hlCMXFkBtRKR3sYeZ0uESjLShVNDqGgwdhZqT1sJyA0whQ2pshYirQnWS75EZcnAhpuwK0O01N0snIzZV7lacO+/btsszK8rnTWFUluTeSTKtt9pzEMZKdLV+xutr6jABx5kbEdhozMuR8OjwjpSshVdjY3I5+0RiEyXAcHJ5qmhKRmpGBqMfe3gk7jQClCSuPPqfR/s9sa4Ovfc016DggSf6LL8K990pIy+9/77M/PRmisakjioM9CVanRwEVjcok0NwsnaBFvZ+IvRgV5dq2YAF8+qn1xr4xH42jcQ6ks1Oecbnm0CQ4Nked09jbK6Oi9mRPh9LXJ+cuY7rVYx2naHRl4OxIlReBngynuVkGP6Kj+/9PBoeo2uFyOTlSoKuqSjIDDyY/X3qWp53mc6fRrtFoNFnX0wScRrD65UlJAeHMjYrtNNrxmw4XwnbzkkOsc+mlaJw5E8LDTSrDc4JPNNpOoyt+2jkcOiQaJz0dt0xw43cabdFYFr346BONTU1yvZ54Irz3Hvz2t+zfL7feH/4Q+qoOwNe/DsuWwRVXwJ//7LM+RE3NMKJxnBlwQR4FAAUs0hBVN1Q0Kj7HjjhY1PCu3BzcmD9fnEbTRIrCgc9j25XxUVYm5yW3s2BE0VhfD23TjhKnsbQU7rkHnnvO3y0Zkbo6MWAyw6wBmNTUcX1OZKSIl5IWy+kKdNHR3CyjzYbhWTS6dxStqIhhE93k58PKlXJPO3DAp/83A2o0gm9EY3Ky4wWWV7g7jeD472T/LJINq51euh0hIZCWZlARd0zwiUbbaTzmGMfNabR1XXo6AweQxsmMGTKduCw09+gbELcLXt52G3zhC5h33Mk3v95CXR388pfw1eP20NXaBX/5C/zgB3Jt//GPE/6zdgCJ67HX3CxTbKZNG/dnDii74XI6FBWNis+x+1uLajYOEY0LFsgc5YMHkVRXsbHWG8Xf2H3nuS3bRxSNABW1EZKmLNDDF0fDHrF0eL0tO3omo6dUxEJExLg/KzsbShutjm6wiEbon+c5+FwOdhphaIjqkSMy2rVypWuOti/dRttpnKhodIXGlRI8TuNg0ejw7+QKT+09KFE24eFeH5uRAZURltM4IKYvwLGdxiVLZITLQYl+bJ2TkYE8BEND+39r4yQrC8p60+XCDvR54WPBveDlgw/yzPQrefXdWO7+dQ8/O3sz62rO4rycXbRkLJa+4RlnSBmjCc4ZrK+Xy2WA0ziB0FSQQbzYWJOC8OVuc6oUFY2KzykogPCwPuayf1jRCG7X4KxZ6jQ6hKIiWea27hhVNLpCVIPdabSzsHnKuukQ7I5PZsen4w5NtcnJgZKa6fImGMJT7c7DSE5jUpLsl50tg1mDM6janXjbaQSfikZfOY2RkfI1XU5jWxt0dPiqmf4hwMJTXU5j94ExZ29MT4fK7hT5HTj8njMm3EUjOKpW4xCnMTPTqr0xfrKyoLRtpoiho2lQ3H4QpafTEjmTW8P/wEo+5qYPvsbt/zqLx1fdz5ufpnPaaVZdxVtukWPWr5/Qn7W7kL4UjYYBixYZFExfqaLRDRWNis8pKIC8mYcJo3d00ZiScnTdVB1McTFETusjFc91/lQ0OhOX09i8e8KiMTsbKqpD6SHU8a7OqLh3HiIjJW5sOKfRDkcLCRk+g6qdBGflSrlnJSf7LISwuVn61C6nMSzMKjY2PlzTxuxkOg4XWaMSoOGpiZ3jFI3NcVLjL5hCVI8cketv3jx576B5jRUVctnPns2Ey23YZGVBWZN1Ho+mENXKSnFqZ8/mxz+G6sbpPHjOC4T9/WmYNYuvv3YFL7xg8Omnkgex+dTzZFrAvfdO6M/W1MjSl6IRrAyq3fNUNLqholHxOQUFsCiqTDo+dryURWamhJm7QsTVafSeqirYuBGefx7WrYOHHpKJ5D4KYyouhtzZHRjgUXikpckInCuD6tEiGh0enlpRIQZZUt3ecZfbsMnJgd5eg8qoBcElGkH+b4ZzGt0TXyxePNRpzM+XQZKMDLkAli3zmdNo/7RcTmNi4rCZi73FJRqTk2VFoJ/DwU6jw79PQ4NoxfCWxnGJxs6uEOrx3aCEI2htlf7AgEm3zqDSShYeFsbQe8E4yc6GlvZwDhF/dCXDqaiA2bPZuTuUe++F66+HE56+BS6/HP7xD0hM5Jxz4J//FH3+8KOh8O1vw7vvwkcfjfvP2l3IAXMafSQaq9sTOVxx2FEh1f5ERaPiUzo7JcxxUcheGVUMGfgTCwmRhKrqNI6R0lLJInTmmXDhhfCVr8CNN0omso8/9smfKC6G3CRLJHkQjeHh0u9Wp9FZlJdDRoaJUXPAJ04jQGns0uAKTwX5v3E/l729Eirn7i4strIe2vNZQUTjihX9Ym7pUti1a2jNx3HgqtHoLhongKtWY3yQOY0JCZIF1+Hfp77e0uuHD49LNAJUzloVXKLxyBERjSkpMmrsr2Q4Tzwx5F7uqtF45Ij0RXzkNAKUkRU8orGnB+66q7+M0XBUVtKXnsmNN8rl+v/+HxLd8fTTklHV4vTTpSvzu99B5xVXS26LCbiNQ8JTx3HtDYedDKeARZoMx0JFo+JTCgulH7WoPb+/9zmIBQsGzWmsr9fiqaPxm9/Q2WVIjaOtW+U/8L33ZJsdOjcB7Prmc2Otu+8IwmNA2Y2jRTQ2Nzt6pLGiAjJTu+U68pFoLJm+2PGuzqgMJxrdXePqaqkX5u4uDM6g2t0truLKlf37LFsmYsYHpVjs5rjCU30gGnt6oNq0fgeBfg7b2iSxU2hoQCT3qa+3IoMPHx6z22GbqZUZJwaXaGxtFcEfEmJN+Cud+jZUVkrtwEG1AV01Gm0h6wOn0ZWQKnRe8ISnfvwx3HnnyJnEKyp4vOcrvPce/PrXI9/KfvhD0e9PboiDa66Bv/993BE9tbUSaeOK6veR07hwoSw/Zb6GqFqoaFR8iitzav3mEUVjcbH0xUhJEcXi8NFjv1JbS/4jW5llHOQPJZ+HVavEdTzhBLlL7tgx4T9RXy/P9dxwa07CzJke9x0gGpuagivL32Bs0QiOdhvLyyEjwUo2McHwVNvtqA7PcnwHfVSGC0+tqen/zdqib7DTCP0hqnv3SgiFu2i0M6j6oGNv9yl9KRoBSlqs8NRAv7e2t0uPEAKijEhDgw+cxqTl8rvr6vJ9A/2BHZ4KI9dqLC6Gv/51ctpgD666DbKappvT6INyGzb2NVg2Y2l/cphAx4682L9/+O2mSW9FNT/ZdxknnST6fCQ+8xnpyvzqV9B707dkpOvBB8fVNLtGo2HQ35/0gdNoP0prmK2i0UJFo+JTCgrAMEwWdGwfUTT29Fj9Na3VOCoH/98fuajrbzR3R/HrX7tl8A4Jkc6rD0SjK3OqWSR33xDPt4bMTHkO9sUnSqfGDh8LRgJANHZ1yUMzM8ZyfSfoNE6bJn30pvCZgR2e2tcnoVSDncaurn6HfDh3ISdHknbYyXDck+DYLFkiPRQfzGusqpL+TXQ0PhWNpU1WpynQhX9bm5SuALHwHC4aJxKeOmuWzK2rnJ4no6rB0lE9csT6gSPXlyfReNddMv9tcCIqX2Bfx/n5rlWHralq6ekMrNc6QZKS5CdbNn1R8IhGOwOuJ9HY1MS/Ok6ioiWBW28dfVq2YYjbWFgI63fOhfPPlzwN48j2XFvrNp+xvFwErj34NwFiYuQ81sZqMhwbFY2KTykogKzZXUTRPqJoBCtE3A5C13mNw9Jdf5gv/eFUDobM5j//U6Zfvfii2w7Ll4tonKDb53peduwZVXRkZorxUhduDcMFc4jq4cP9Tz+HisaqKjn9GeFWCrkJikaQ+ShNhvNDAUfE7uTExvavG1yrsbhYBkjstMAgTvvChbBnj0TN5+eLirZvXCA9iXnzfOI0Vldb8xnBJ6LR/iqllWHy3R0uskalvb1fNCYne/5NlpWJsPdzkpWGBkhK6BWxO0bRGBoqP9GKPut3GiwhqoOdRju0ZTCbNslyUAipT7AHV2trXffyATUaS0pE2NoJpCaAYVhRuCE5/amtAx17LqMn0VhRwWNcQ2JMJxdc4N1HXnyx5Lj4xS/A/Oa35Hfx97+PuWm1tW7zGbdtk+WqVWP+nOFISYHamLkqGi1UNCo+paAAFqVYIsJDmMf8+bLctw91GkfhOxfs563eU3jkJ9X8+McyInr//W47LF8uwmaCda9cUXqHt3slGgHKe44C0djc3P87dqhodNVoNKzOia9Eoxkvw/B29spAww6nGuw0Qv+5LCmRi2pwAfbFi3loywoSEmDzxh5x9ENDB+6zdKnPnMa0NMRZammZsGgcUKsxAJy5UWlr6w9PHen7vPuuuEnPPjt1bRtER4dooeSYTlkxjhC59HSobJkhv8lgEY12IhzwnEG1okKuxxkzJGGNr58rO3b021GW2zigRqOdOXUCmYvdycqCsu458kdc4UEBzCiisbGglue4iCvPaWTaNO8+MjQUvv990Xn/4iwZrLvvvjEPgg8QjR9/LB88qNzbeElJgdqwNHE5gnkqjpeoaFR8Rm+vCMFFsdYknUHlNmwSEmTK3L59qNM4Ao891MX976/iO1nP8JU7sgkLgxtugNdfdxv0WrFClhMMUS0slI7r9JqSUefEuURjhyX4g1k0Hj4sojE83LFlN1w1GjuL5OKKjJzwZyYkwKFey6ELVLdxBNH4vbvTOOccOLi3cdhwtL/3foGbmu6itRVu3vnv9CwfZtR62TLpQE0wQVJ1tXXJ2WJogqIRBpXdCNTzZzM4PLWpafjEafbI15tvTl3bBmGfwuTp1m9ivKKxKkTC64JFNNqJcMCzaHzrLVnef5DdVKIAACAASURBVL8MVD3yyNj+xkgd+tZWuVavvFLeW6Gq//qXhAMvWIDPajTaZGdDWUui/FaDYVDcdoYbG4d95v/luel0EsnV14xNVlx1ldyWf/FLA775TUn098EHXh/f0yOzKAY4jYsX9w80TZCUFKjtTZbv79A+wFSiolHxGWVlMtK6KGSf9DpHeGC6MqjGx0uHPBhuqj7kgw/gxm+F8hle55eP9ofLXHut/Hc98IC1YulSGRmdoGjctw8WzO+Tu6+3TmNLgrwIdtEYHz+0VIODcIVYtRb4xGUEy2nssjrqgSo67JHxQaJxPRfx21eW8MorcEL+g+yOXzvgsNdfh688cxFreZd139rCJ31LeLD5iqGfv3SpdFQnMP+qr09+Vmlp9M+v9BDWPxZcojEYnMbBiXBAhONgbNH41ltWlrWpx/6vTppm/fbGIRozMsScMo+xyroEA+7hqbYwG040JiTAFVdIPYb77x/5PHZ3S93i735XOhQpKZ7LQXzyiVyrp5wig0T5+XR3w5NPwnnnQVKilT7ch6IxKwsajkynlejgCFF1/78dxm18/K1cVpDPys+OLbx32jT4zndEwH+05OsSUj8gnGpk6uvl1KamIi+2bfNZaCpYorHNGkDVEFUVjYrvcGVO7fBcbsPGJRoNQ0JU1WkcwLe+aTLbPMBfj/stYWee6lqfkgJf+hL86U/WwF90tMytmoBoNE1J1Lcww0poM4rwsMullR+yOuPDdeCCBTuZhYNFY3m5mFPRdaW+FY3tlmMZqMlwhnEaa1qiud54hFWzynlvYyedvWGc+PKdvPKKbP/oI5lns2huNy9wPpeX/pzP8Sp3vrhm6C3KDn+agBt08KCMlM+ZQ3+HxI7fnwDZ2TKY0JM4K3BFv81gpxGG/072/NTWVnEr/IDdrOQwK4HWOJ3G9nZoSpong6mBHhJnmgMT4cyaJdEQg2s1btokoi4kBG65RZTz+vVDP+/QIfjqV2UAwRaXsbFyn3rnneHbYD8fV6yQea/5+bz8slx/11yDHNvW5pMkODYDajUGuWjcuRO21aRx9Yz1Q8P4veD662Vs9j9+HE3LlTfIvMaaGq+OHVCjsapKzuWxx465DZ5ISYH65nB6CVHRiIpGxYe4RGPTe16JxoMH5f7PrFnqNLpRXg4fbTW4sfc+kv7r5iFzLG6+WfrDTz1lrbCT4YyTgwdFGy2YaQ2TjyI8DMMqu1Fnjf4Hu9M4Y4b06kcKTdm+vb9u5hRTUWG5v67JcRMnIQGaWq15foEqOgaJRtMUp76VGJ5c8TtOTCnmQ1YzN/UI554rJcjOOUc6Ca+8Hkp8RDvGKy/z+5DbaOsM5Uc/GvT5ubkiZiYwr9H+SaWlIXNmwsJ85jT29EB1ZG5wOI3uiXBg+O9UVCQnEPwWouoKTw07JC/GKRoBKkKyxE1zcH1Yr2hvl4vPdhoNY2jZjepqESKnnSbvzz1Xrq/BBd9bW2XbX/8Kl14qorKhQVzK8PD+RDqD2b5dVElmpojGoiIe+99uUlKsn4wPy23YuMpuBItobG2VQRvDGCIaH38cwo1ursj7aFwfHRcHv/0tbN4Ma974KZ92Z8PDD3t17ADR6OMkOPbn9vUZ1Edlyej6UY6KRsVn7N0Ls2aZJFbsGLXjYw+muzKoqtPoYv39Mif04vl75AE5iDVr5Ln3hz9Yg9DLl0uHye4kjxF78GxBjNWD9cKtysyE8upQeVAHq2js7ZUHpTdO4623ikU13FyrSaa8HDLSTRGNdnXwCZKQAM2toTK6GiSi8ZFHJPPwr+Y9wqLWj6CkhHSq2PxoIeefL9n+w8LgtddgdkaYJGXo7mbBohBuvdXgsccGTbUJCYFjjpmQ02jXaHSJxtzcoUl5xoE9dnAgLEP+HwK53t/gRDgwVDR2dMh/5urVcj/0k2i0O7AzDeuamYBorLQzqAa66LdFr+00wlDRaM9ntEVjaCh8+9syEPeRJUQ6OuDCC2l6fy8f/OQVeh9+FC66SMRodLSce/tzBrNjh0QGGAasXMlBZvLiq6FcdZVc874st2HjchojFwaHaGxpkUGbjIwBorGrSwawL4x+g+Sc2BE+YGSuuUbuvbVN0zg+LJ8X7ikaet/q6ZEEDG4MEI0ffyz35eXLx92OwdhzJWszj1enERWNig8pKIBF87rlIT/KiJ2dvd6VQVWdRuHDD3n2d6UcE7aX+S/8dth6iYY1X3zXLnj7bfqT4YzT8bAHzxZGWA9Ob0VjuSFxkcEqGt1Fx+zZEobrqYbUvn0y8PGvf01d+ywqKiAz6YiIXB+KRoBDRmJQhKfu3w+33Qaf/SzcfNwHMgBgdRRjlmTx7LMysL1pE8ydax1v1/lasYI775SfwM03D0qEuHSpiMZxhhDaTuOcOYho9EFoKvSfv6bwIEhW5U14almZnIPcXAlZfPddv2T9raoSzZ/caz3PJiIau6xzF+ii0U6gYjuNADk5FBXBWWdJEfjf3x/Cu1Gf5UiePMt6eqD67GvYFnUKL/zH2/ziZz18MWcruW8+QqLZwJrbz+Tuuwf9ndNOk7DkwfMae3vl2Wg/J1es4Cm+Qk9vCFdfbe3jw/nENqmpEBEBZbFLgkc0xsTIdBg34fbPf8rleHXXwxN+/px1lpiF87J6uKDpz/z35Z/S12dt3LIFjj9e7pEf9TuadhRraipy8MKFAwcoJogtGmtSlqtoREWj4iNMU0TjwhQrLGeUm29urgwmujKoHjwY+HM3JsrmzdSeeTmbe0/kkptSR+xAXnaZdAzvv5/+UbVxhqju2ycD+Rmd+0WRutKQeSYzU05Ze/zswO6QjsRht3lJdkbZ4dzGlpb+J9e6dVPTNrc/fegQZERZHUv3eoMTwCU6EnID3mnsmR7LVVdJwoXHH4eQOan9onH6dEhJISQErrtO+hsubNG4ciWxsfCb30if5LHH3PZZtkw69aPNv+nuHrbId1WVjAulzOyTjpivRWOYFc4ZqOcQvAtPdXeKzjpLCsm+//7UtdGiuloGF0Jaxj+ncfZseTZWtllZdINQNHamz+VLhx/mww9NXn0Vbnnvy5zc9hpxCaGkpMi1mrYwluPa3uaCt77Lj+4I4+Oa2aw61uTnP4eTT4Zf/UrGE1ycfroIxHffHfj3i4rE7bSek2bqbB4LvZ4Tkov6678XF8tzz4diIyREBgAqwucGh2hsbZW5o3l5A5zGxx+H2Sl9fK7rhf4RjwmQlQXv7IjlqzHP8j/PHsP3v9UuN+cTT5QBzPBw+Mc/XPvX1sptPCYGcRp9GJoKbk5jwkIZnArUElQ+QkWj4hMOHhQjZlGcFW81imiMiJDnu0s0dnaOO7wyKHj9dfi3f+P5mCswCeGSa+JH3D0qCr7xDZnScSA0XXqJ4xSNe/fKcyCkplo6ZV6Ex9napDJ6wdEhGgfX93PHfoDOni014qZwDpKrRmOYZVn5yGmMt35+TXFZgSs4mpshKopnNoSxZYuEc6elIQMAHR1Sqy0nx3NdNjvRzXHHAXD55ZKn44473AznpUtlOZLLb5qS6n/x4iFOdVWV3P7Caiplmx2CMUFcotG0XgSy8HAPT42KEkUx+DfpLhpPOUVUlx9CVKurrd/Y4cOS7CUiYsyfERoqt5KKw1YCp0A+dzBseOp/bL6Aj1nFU3eVcSC/hkrS2PC1Z7njDrjwQrnGHnwQnnvwAB9wAo0kUPSb5/jHtrn88IdSDL6uDv73f93+zkknSazp4BBV+7loicat2wx29y7k6si/9O/j43IbNsnJ0BA6MzhEY0uLiMZ58+T6O3SIAwfgpZfga+fWEYbvIl2mR4fwp5+U8e88xG8fmM7Gx0rge98TZ+LMM6XjY5o0NsIzz8hYm1FzQJ7PPkyCA26iMTpH7uUe6lQeLahoVHyCKwlOmBW24KFGozsLFlhzGmdZYThH67zGDz+UvN/z5vHs4jvIzfWuLu3XviYDq8+/YEwoGc6+fZbDcuCA19k3XWU3IuYFb/ZUexBjNNH46aey/NGPpIP0/PNT0z7cajT2llovfBue2hSTEdjhqXFxFBSILvzCF6z19rn84IOR5zCdd570iE6V7MWGAf/933Kb+tvfrH28EY0PPigj462tsHv3gE0ukWH/hnztNPZZTlegCo/ubolVtJ1Gw7B64oO+T1GR7JOSIuHkxx/vl1DxqiorKMFOoDVO0tOhstESyoF67mwGOY3PPAP3vZLHrdzNhTk7MTa/TRrVXHBTOj/5iYSJ/+QnUpP4whtms/pnF5Jw/11SWsNi7VrRDr/6lZvxEx0t531wMpwdO0SJL1kCiDMWGdbNZTX39M+ZKy726XxGm8REaDQT5BwGekIj9/BUgKIi/vIXKRv09eOtskM+cBptjGuu5rfJvyBvegVfm/USh+/4tYjWiy+G/fvp+2Q3V10l99CHH0ZcRvC50xgXJ+NUtSFWtNFRHqI6ZaLRMIynDMM4YBhGs2EYnxqGca21PtswDNMwjFa3f3e6HTfNMIzHrONqDMP4zqDPPcswjL2GYbQZhrHRMIzR1Yric1yisWuH3Cnda6N5YP58icjqm2kP5Ryl8xpffRW6uji0fiP/emcal1zi2fxwZ8kSmX/13HPIfI2dOwdNuBqdzk4ZZF2wgPGJxpDso8NpHCk81Z7fcfXVItpcaW0nH5fT2L5PrrkJdFTdcc1pjJoT2E5jXBwlJSLMXKaP/Rtvbx/ZXQgNldSKbhfjmWeKYXjvvVY0fXKyfMZ99w0/Ap2fL5Mp7Y6MVVTcxpXw1seicdo0Meeauq2QwEA9h7YicC/UnZQ0vNOYm9t/rs46S+Y9TXH0SnW1D0VjrfWDDXTR6OY0FhdLhMzxK7v5JT+QZDhvvSVixJNDdPvtMpl4EP/1XxIV/sc/uq08/XTYupW+5lZuvVWmcex7p05GRSMjaW+Hp5+GL6ypYkZPgwzi2KHjk+A0JiZCY5eVHGaY8PSAwg5PtUXj/v28+ab0HRZgCSkfDVoCEB9PdHUhT27MoLougm99y1p/wQVgGPzstnpeeknuxatXI3MHDKN/7qqPsGfs1PZY4eIqGqeMnwPZpmnGARcAdxmG4T4kEG+aZoz176du638M5AFZwBnA9w3DOBvAMIxk4FngTiAR2Ar8DWXKKSiQ+376wY+9nky+YIH0CSr6rFR/R6vTWFsLCQm8uCWJ7m645BLvDjMMCeV5801omb9K/jPHGDqxf7+MFI7VaUxLk79f3pd+dIjG5GQJfRqu7EZhofyHxMRIYepXX50yd668XObOzGnc5dMHtsupikgJXMFhicbS0kH9QXsAAMbsLhiGJHXMz3ersPL3v0uH6uSTB2ZSbW6WoqozZ8LLL0uHKz9/wOe5RMann4pT4qM6m2CVTekIcLfKnrRmO40wvNM42Ck680wZQNu8efLbaHHkiNwyXOGpXgyceiI9HSqrDMzYuMA9dzaW09gVEcNll8mqv/1fGBFR4f2ice1aK42p95x2mgQB/OIXblHfp53G/2fvzMMjrep8/zlV2deqpCpbL+klTXdDI400IM2i4HYHQXDhDos6ouJyXcdRR0fFcRl1ZnBQ0XHjXkW9o6KjoqIgXHZQhwaUAbqhu+lOL9mTylJLtqpz//i975tKOnuqUu9bdT7P00+lq7Kc5NT7nvM939+iJyf50LV9fOUrcqB6yv1f511jX6arS/4/NATXvs3qJfjEEyLmksmsiMb6ehiw+916XTTa4anWdZZ89gAPPWQFYhw9KodsTU2Z/ZnFxZx9toQr/+AHVipjczN3bns/n7rnAt74RnjHO6zPfewxOXSrXn4F17lobITu/mK5MI1oXB201k9rrcfs/1r/Ns/zJTZvAj6rtY5orfcC3wHebL32WuBprfVPtdajiMA8TSm1bdbvZMgae/eK8FDthxd983UqqA5ZN5pCdRq7u6GxkZ//XPaMZ5+9+C+97DKJsLlj5Fx5Yokhqk67jS0pGcciN62lpbI+HBlvlE3B2NjCX+Q10kWjzycrx1zhqbZDdM01sgH5yeqcXR09KqKj6Njh7IjGorCIRqeEnYdIE43TzrHS3+PL2Ci+4Q2S83nTTdYTu3aJOCkulp3sI4+IDfmOd4iN/6MfiXA87bRpTuPoqOgBx2k86aTFhRgskmAQIiNFIri8KvxtpzFdNNbXTxdSWp8oGs85R25SqxiiOq0S7gqdxnXrLBEa3JA3ovGjX23h0UclPHTjJqtX43/9l7h9dquNJXL99fJ3/+53rSfOPZd/Vh/jxp9v4L3vhSN/HuBdfIObn7+QtjYxLVtb4cJrrEO+P/95qnJqlsJTB6NF0rrIy3mNyaQc4FRVybW4di1P7RllaEhSiDl2TN74fn9WfvzHPy6Rx+98pxRRvbr98+zgKb75sfapW2YWiuDYNDZa29OtW41oXM0fppT6d6VUHNgHdAK/TXu5XSl1TCn1XctBRCkVBFqA9J3wX4BTrI9PSX9Nax0DDqa9blgl9u6F7ds1J+7Q5sauVLivy6q6UahOY1cX8dB6fvc7CdefpcvGnOzeLQfvv3x8vZzULlM0nlTfL7lD6S7MAqxfD0dGrXzUY8eW9HM9QbpoBPnbzBWeumWLfHzqqZKQukpVVI8csbTi0aMZFY3l5bLnjvjqZcNg/y28xPAwE1VBjh2bcUuqrp4qyrEM0VhZKSF2P/tZ2tt++3Z46CERhy97GbzrXdKA/DOfsXZVSHPVv/zFEeDTRMazz2YsNNUmGLTSjWeKLC9hO43zhaf29orCSt/0l5eLe7WKxXAyKRrt1LCjVdu9O3c2VnjqzT+u5KqrZI0D5KK0K52+5CXL+tYXXSRr4Be+IIenN/+4io/pz3NV6Pd8+cvQ0PFnbuJ9PHPzH7j4YtmeXHcd+IqsXn5PPDElGrMUnqq1ktZFXhaNdoix7eK1tfHg03Ky6DiNGcxnnElxsTiNiYRc1pO+Ev6T11Fx5y/kE3p65Ga8WqKxgCv9r6po1Fr/L6AaOB8JKx0D+oAzkfDTM6zX7R2XXaM5fccyZH2O/frM3Uz66w5KqbcrpfYopfb0erWww2I5cgS++c0l57ctl+Fhyc3Zvi4qx+eLFI0NDXJiv2+/XzYCBew03pl6OYnE4kNTbYqKpF7H7Xf4mdi6Y8micd8+cTqqR6wdzxLC49avhyPDliWV3qg5XxgaktWqtFT+39x8YnhqJCKbOls0griNf/zjiaHCg4MSyphBV/boUVi/JimLZobabdgEg2mFVLx4zxwe5qivlVRqlluSfTiyzI3iu98t2u+b30x7srVVhOPWrVLW8RWvgI9+dOr1nTvFdTl4EJh6K60Jj8v1ky3RGArll9MYCklIvO1+W3/PE5yiiy6S++Eq/e7OfNrhqRkQjcfK2rwvGqNR4pQzMqKculHA1LVXUeFUKF4qSsEnPyn3wb/5GzH3X7nxWb4XuRxfIuash1su3sKtt0rHBOeS3LlTnMaDB2UhzYLoqbPS4AYatnlbNNq9L9NE4wPH21i3zqp5eOxYZvMZZ2HrVrjxRjlUv+UHfrbsKJMqqjBVBCfDlVNtmppkCUxt2SrXdqHuVclB9VStdVJr/RCwFniX1jqqtd6jtZ7UWncD7wFeoZSqAayyW6QnB9QAdvfW6IzXZr6e/nO/rbXepbXeFQ6HM/kruY+bb5aT7uuuW5WwMrs5/PZay4VZpGhUSg7o9+1DFGShOo3d3fy8/8XU1TmFGpfE5ZfLfez+pr8+odDGQjz7rBUm3LFM0dhbhob8FY21tVMhg83NJzqNdhGcdNF41VXyNf/xH1PP/eY3Urnor/9aQufsi2YFaG0ZjLVWsY8ML9rBIEQmrU2CF0XH8DCHtdRFO0EbNjeL+Fhm/svGjVKP4VvfmtFFo6FBqjd+8YviNqeHDZx+ujxaeY3Hre5Ea1JH5T6dBdE4MEB+Oo2plBzCwPR2G+lcdJE8zqymmSXs+cyk03jM3+r9nPFYjJ4SuTdNawFs7xN2715Um6e5eOUrJXTxxz+Wx//8tyOUJBPSp/PPf5Ydv/WD169Pi6A8/XQ5xLnrLnlhiTmViyHvRKNVAVdvbuPBsTM5/0UTUwtRFp1Gm3e8Qw7CLr8csawfekjU3GOPySfY99gM09goHkx/8w55ooBDVHPZcqOI2XMabd9Xaa0jSBjraWmvnwbYdcufTn9NKVVpfc/pdc0LjfZ22ax897vw9rdnXTju2SOPp5VZF9IiRSNIiOq+faT5/wXG6Cjjwwl+3X4qr3718tbOl79c9lS3jb5Cdi6L3CBqLX97p3IqLFk0jo756PM15rdotGmxKonaZdph9qqX69ZJjs4Pfyif/4Y3wKWXyg7ipptk8/DCF4riWEGYS2+vmJbry3unfm4GCQYhMm45PF4TjVrDyAiHJ6TI1gm3pEsuEQG/At73Pvmz/PjHM16orYW///upRvQ2J58sG1PrYMcJZxyxY8Sz6DR6XTTOdBph6neyRePMk4Ezz5RDgVXKa+zokNDl6oqkiJEViMbmZjl3OsZa786dTTRKd5kc3swqGpeZz2ijlNxWr74abr8dKl/6IlGG990nTuNpp83+hbbAeOyxrOQzgpxvAPQH27wtGu22KdYh28Gq0+iimQu2dMqhxuho1p1Gmyo7/vA1r5G97a9+JU5jW1vGqofPxOnVGLALcRjRmFWUUg1KqSuVUlVKKb9S6pXAVcA9SqmzlVJblVI+pVQ98FXgPq21HXb6feATSqmgVeDmOuB71mu/AHYopV6nlCoDrgee1Fqv/Bjfy7S3i5vxyU/C//7fcjyTReH4yCOyyG2IWVp9iaKxsxOGAq2F6TR2d3MvFzI0Wrbk0FSbigoRjrc9t11OXBYZotrTI7rIqZwKSxaNAEcadk3lheQTM0Wj/bfp6pp6bv9+OaCZuem45pqpXMef/EQa/D32GLznPdLT77zzJKv/ta9dtiBzejT6LIsjw4t2IACRuBWa67Xw1LExmJjg8GgTPt8sh+Af/jB87Wsr+hEXXijm8Ve/ukjtX1oqX5DmNJaXQ+C4dd9Md6szQDAoe72JQNh7ot9mrkI4QOT5iKTaPv+8xISWlU3/2qIiCd24/fZV+f3tnptqJK2/6zIpLpbbzdGJJnFUJyczNMocEI3SUyr3JrslMyCifs0ayzZaGWefLcZ+fT0ibM44QxzEZ56ZuwXDKadMuYtZyGeENKexar24cV4sKAYnhKc+0C9lQ84PPTNVFXYVnMZp7NwpsbG/+IWsrVnKZ4Q00ehrlvuMEY1ZRwPvAo4BEeAG4ANa69uATcAdSEjpU0ie41VpX/sppLhNO3A/8K9a6zsAtNa9wOuAf7K+79nAlavw+7ib9na5mD79aalVfPPNskFNpSR+/yc/gQ99CC6+WHpZrZCHH5YIE9V+WE6BnaOghdm+XR73FZ9amE5jdzd/4ByU0rz0pcv/NpdfDkd7y3mC0xctGp3KqVsR0RcKnbjxmgdHNNbvzE+ncXh4dtGYHqK6f7/8Iey8R5vXv15U1+bNsqD94z9ONQpsboY77oAvfUmax1988bKG5/RonLSclgwv2sEgRKKW9e010WH15zs0EmLt2hVFv82JUvDe94oG/MEPJBrO/vf0XLEudh4VU43g1f7npICOXbI2Qzi9NqvWeld4zBGe2kEzm1+/k0AAGv/vlzh/5Hbe+la44YYZ+7n3v19Ox846C556KqtDtefT6Q25Qtdj7Vo4lrCsqkhkZYPLJbEY3UXi+E9zGltbJRdux47M/8wXv1gqs05MzO00lpaK+w9Zcxod0Vi+Rg6yvHb4ZjMjPPXBA02E6GV74ompamCr5DQ6KCVu4+9/L3ve1RCNvT6JCDGiMbtorXu11i/WWge01jVa61O11t+xXvuR1nqj1rpSa92stX6T1ror7WvHtNZvsb6uUWv9bzO+991a621a63Kt9Uu01odX43dyLcmkXMStrXJRfeYzUmf6O9+RvlFtbdLx9mtfk7CdG29c0Y/r6BC9cO65LKlyqo1TQTW5RZydfGzdMB/d3exnC+ubxqcdpi+VSy4Rw+u2ymsWLRrttLpt25Cd7llnLelnOqKxYnt+isbZwlPhRNE4m0MUCMhC9qc/STXVmfh88MEPwsc+JvHddnW6JeA4jSPPiOhI31hngGAQIoM++b4eFY2Hh4LZMhEAiTyuq5MiHLt3T/3bsUNuuSdw+uniVHd1ceTIjHYbGcZpm1LWLFaoF4XHLE6jrg/xLr5BYszHZz8Lry6+A1VWxu23i4G8bZtEf//rv8LRbS+HBx6Q8LlzzoHbbsvaUJ2emzOrLi+TtWvh2Ij1PbwcohqN0uOXtlrTnMZskl6NdS7RCFMhqlm6SQQCsg0bKLZUh1dDVGeEpz7wSDHnle5BHTwwJRpX22kEEY0TE/JxlorgQJpoNG03cprTaMgGHR1yotwqOQQoBZ/7nIjEq6+WPKrHH5dN1ZvfLPHg9mnuMrAbXC9XNG7cKC7A3rilQAotRLW7mwO0sWXzysJWwmGZg1/6XiMCcBHxcs8+K3pgXVVEwnh2717Sz6yvl68/4t8o77t8E/xzhafaolFrUs/uZ2TDqXR2ylt3WvRRTc3Cfate8AKZq717lzy8o0fFGA717s3KKW8wKH+CVH3Yeyfktmjsr17qLWlJVFbKucAdd0z/d+65clZn12pxsELl7v9+O488IiGuPPfcVNPaDOKIxhJrx+NF4TGL03jrA038isv47Csf5hMfGuU78Wt44N0/oatL3L4bb5Q15SMfkYOt137xLCb/8Kioyde8RvozZLhkvtZT4amZEo3NzdA5bIllL86dTSxGN43U1CwpkGVlnHeeHMyVlc1/IJNl0ej3i3Ds15bl6FXRmBaeevy4RIRfsOaAHJoePSq/aFPT6o/r3HNl8wNZFY2BgAQKOaLx0KHptQ0KCCMa8432dnm0RSOAUny/+t386MJvS2Gc00+XK+DKK8XhihR/IQAAIABJREFUuP32Zf+4hx+W+/LOF6SWJRqLisSo2TdgbWwKUDTuZwtt21ceP3fZZfDkyCYOPTcO//mfC37+s8/K3973X3+UJ5YoGpWyKqhOtkxVUMsnZorGhga08nHTbetYtw6qqjT+kUFqvvMlWlrkNLK0VPTbWWdJyPDPfrbA/tQOzVpG6Jzdo1EdO5rxdhsgokNrGK7b4EmncZxijg+UZVU0ggRvvPKV0//ddJPs8z/zmRmfvHMnExTxv760iQ0b4CPvHBbnMZtOo88KcfTaHMIJhXD6+uC9f1/OLvbwgVPumopwsMILW1rgAx8QIX/ggAjHX/wCbrx1jTiOV10lav6v/srJLc0EkYiYmZl0GuvqYChmNYb3smiMRulJhVfPZQQ5sDvrLDmkma8q6jXXSOpAFgVHXR0MJK0i/14XjVVVPPigfHj+KRG5yI4dkzf+Qgek2cDvl3CPF74w4+H96SglLnl3N3IylEx6836aAYxozDdmEY333ium4jXXyCm4wwUXyOnQCeX/Fs/DD8u9uSTSLU7TMnZo27fDvq6A/KfA8hr7D48QoY4t21Ze7vuyy+TxtsZ3SC7rAjlM+/ZZoakPPyw33yWGp4IlGmPWKWo+haimUifkNMbH/Lyp7Ce8785L2LIF3n5pJ9fzaf71LXv5xjekIMqHPyy93YNBSV274gpp1zenkbh5s5y6LEM0HrW1oq0eM4wjOmpavbdADg9zhPVorbIuGmfj9NPhbW8T8Titu0ptLTcGP8szPWFuugkqjlstW7IpGrE+8KLwsMNTLYvqb/8WIhHF/6n7EEUDPVOVUzefWIh982bpfHL55XD99fDc0XKpaPyVr0i+2wtfCP/zf2ak/Y1TCTfDolFrxRC13pw7m2iU7sn66fmMq8GPfww/+tH8nxMKSZGyLLTbsKmrg4FoiYQlePVg1Q5PtURjVRXsPKtEom727Vv9fMZ0brhBrucs4xT4t69r+zovMIxozDfskyzLeejvhze+URyl004Tc9FuLYffL7va22+fSt5fAvG4HNY6oamwLNG4bRscOF7GOMUF5zQeeF4uwba2lX+vtjYpCPfL0FvFRvz+9+f83LExibDYuhWJMd65Uxa1JbJ+PRzps0Ko8kk0RqNis9XICfGhQ/I+/7+J1/LZk77P3XfDv/2Pu/g0/8iHPlrEO98pRVE+/3npdHPnnXII+7WvScriC14ggnJkZgdZv1+KMSzXaWwal2s3m6Kxap0nw1MPswHIWuTZgnzuc2KQ/d3fTT135Ah8evgDXFZ5N5dcwlRuTDZFo7Y2OV4T/iCLTHk5KMVvfyua7x/+AU5t7pPFba4ejRZKwb//u0QAXHcdpLSSXinPPy/VxX/3O7lpXnvtitI0bNGYyfBUp4gKdd4WjbEY3ePB1XUaQQ7Oc3FiNIO6OhgYsMNyPOw0VlaCz8eDD0pQUtFW66Dmscdyk89o4/OtisvpiMaAZXAY0WjIC9rbJdmsshKtZaHs6ZEDt1/8QnI9LrssbfN65ZWiIH71qyX/qEcfFTNr926mBMMydmjbtkEyqTjI5oJzGvcfF8GVqWr7V1wBDzwTov20V0vYzbTO41McOCBm2ta2pMRyLTE01Wb9eujqLWLUV5FfbTfSNn533QW7dslb/DdnfoZPVNwoPdufe05OqOfYmBQVwbvfLZ/2N38jB6InnzyL/tqxY8micWJCDnnXV1tJc9kUjeUt3hMcaaIxV/vGhgZxuH77W9EmIMU88fn4SuxtcjDx3HOibGZxylaKM38TVjVrLwqPRAIqKhgels5Rp5wCH/84ssb19Yn4q6iYt8JKczP8279JdOq3vmU9GQhI7PDzz4uI/N734JZblj3M41bXm0w6jc78+cPenDubaJSesZrVdxpdQn29NX1eF41VVQwMSMeoCy5g6qQ7mcyt07hKNDZa3bbs6/qEhPXCwIjGfMNutwF8+9siFL/wBYnE2bABbr1V9ilvfKNVtONFL5Kb2TJCVB9+WB5372ZKMKTnUi4Sp+1GyWmF5zT2BVCkMlbx+2/+RkKabtl5o4TCfPObs36ebXBs8z8nJ+zLFI32XvdQ0zn55TRaG78+FeaSS2Qz+OijcPHOjqlCOPv3T1VymodwWLre/P73kv7x85/P+IQdO2TXOV91yxnVVY8fFyN0Xal1vWQppxGsQirDw94qdGSJRr9fi/uTI977XjkQ+tu/lXvxL38J1199kFba4ckn5Wbc2pqVCiFlZWLSRaIlYrV5UXhYTuMXviBu3v/5P1bnGnsnfvCguIxKzfttrr1WwsY/8pEZ+/ZwWBRlczM89NCyh2k7jc3NyL2jpGTFczqtx58X5w5Aayajo/QnKlbfaXQJ4jTibdEYjUJ1tbPnO/98ph905dJpXCUaG61id9UmPNWQT1ii8ZlnZKPy8pfLo82FF8oaedttVpEGn0/yOu6807qzLZ5HHhHBV1eHCIZweFkhjnbhwL2VuwrPaRxuZH115IQ2f8tlwwa46CL43gObSF30Mvinf5olJjItKq7zAflgmaLRPmw8UHdWXorGvUPNjI+LS9jWhuwKe3rEYp+r3cYcvOxlojF//esZL9jFcOZq7vfkk+KM/OEPzlNOj0asHOZsOo1FVnU6L21ch4c5pDazbl1W05UWpKRE2nE++yz89V+L0/y310vZep54ImvtNmykbYqacua8RjwOFRU8/ri0YXPSrkOhqfDURZy4KSWHqKmUtCyeVpxKKam2uULRWF9v6cShISesfSXYojFSuXbJa7NrGB2lT9eh8RWs01hXJ6ZUcs162d/MEf3jakZGoLqaBx6Qe9pZZyHvcfskoECcxslJiCjrwjSi0eB5tIb2dkbXbObqq0W/3XKL6MJ03vtecaQ+/WkJneLKK+Vq+MUvFv2jUikRjY7WWEblVJuqKjmo2uc/ubCcxrEx9k+0sqUhszeft7xFjN/7X/dV2SjO0otz3z7Jv6l+/H75YJk3fUc0Vpyal6Lx4GAISDtUbbZ63nV1LVk0KgWXXirtUaelTy1UQfWOO+T6TFObTo/GsYNygdvtQDKInbrhLJJeEh3Dwxz2b2LjxvkdqNXgkkukGNLEhOTXlWxcI6JntURjhCmR5TWs8FSnnYVNenjqIsM0Nm6UqJvf/Q7+4z9mvHj++XJRLdMJOn58qo3rCVWXl4l9aDNQ3uLNuQMpgoOoxUIWjVrDUMhaROy+hl7CCk998EERjI6Jbq9/BeI0AnSPWgdCJjzV4Hn6+yEe5xtHL+Evf5E0jdn2kkpJ1OKOHZInMrLlhbIrXkKI6r59shk591zriRWIRpC8xn2TbYXlNPb0cIA22tZm9uTxNa+RQ8Dv/nG7/OeGG07Y8D/7bFoRnN27Fwzvmou6OhEXB3RbfvVqtApDHeyrxedLi7q2d4aPPy7Kb4kb/ksvlYPmu+9Oe3LtWpmwuUTjA5YbfO+9zlO207hu+GkZUxbstMpK+baRlLUB9lIxnOFhDutWN9TBQCnJKf9//w9e/GLriZ07JbpjZGR1RKOXncbycjo700QZiAienJTXlxDb/+53S1GqL395xgvnnSePy3QbOzqyKBqLm7wrGmMxehA3qlDDU+utjjf9NVa9By+GqEajxMpDPPaYlc9oY58aF4jTCNA9XCGFd4zTaPA8VruNO9u3cfLJ8KpXzf2pZWUSrnP8OHzyeiVu4z33LFq0PfKIPJ57LmI7trevSDRu3w77YuvQ3YXjNPY/2yftNjanFv7kJVBRIe3IfvYzGP7o5yUf7l/+xXldaxH9W9dGZd6WGZoKsv9ta4MDCcsG8OKCOBu209hVwfr1aWmL9imMLeSWWMHoggtEH04LUVVq7mI4yaRsZP1+Saq0Sp//8Y8iZKs692cln9EeVjAIg0mrkIqHRMdYJE5HsskVohHkcOWii9KeOP30KcfBOI1zk0gwVlZLf/+MA1B7Jw5LKiJkt3Xbs2dG3a5TT4Xq6hWJRscJzZBoLC2Ve3nE79G5A+M0kpabWmG5cV5cI0dGeCp1MpOTcPbZac+fcw5Ok+I8xxGNPUqubyMaDZ6nvZ0Jinjo2RAvecnCn37OOZLfcdNNsOfUN4v4W0RTeJAiOKGQtWfu7ITx8RXVtt+2DUYmyunoLbYq9OQ/B56UGMUt2+cvpLIcrr1WIrt+8pdtcPXV8PWvO6G/PT1yv9vms3qvOHbx8mhrgwMD1rF4vlRQtUXjsdLpe1J753r//fK4RNFYUiLN33/zmxlvc1s0Tku2QkrVDQ3JTtcSkKOjcNdd1qHQ0aNZPeUNBiEyarVU8ZBobO+T3Gq3iMYT2Llz6mPjNM5NPE6nEgtvmtOYLhqXWEXs9a+Xx2lLXVGRLIjLEI3JpESrZ9ppBKuIirJabsy8N3gB4zROicZiS3V4VDR26iZgRiTq298uv88qtLzINY5otHs1mvBUg+c5coQ97CKW8HPhhYv7ki98QS6G677YxuT2Uxcdovrww2lRjXbjxxWGpwLsS23xbtL/Etm/dxKAtp1VGf/eZ50l7u13v4v0IxsdlTBVpirLbx/6o5RXTN/ALoO2NjjcZfXZzJe8xqEh8Ps5eMg3XTQ2Nsqb/vHHRQEuQ7BdeqlsMh97LO3JHTtkYzjT6bcdzY99TOzOe+/lvvskKu+SV2lxq7ItGuMl8h8Phace7pdiM7nq0bggp58uj6WlWXOKYYbTODDgvQO5eJxO5KDmhPBUmyWuOxs3SlGdn/50xgvnny8HN/NVMZ6Fnh4RjtkSjZFUrYT9r6CPZM6wnMaS4lSm/iSewxGNI8XQ1ORN0RiN0qVFNTU1pT2vVEEIRpB59PvTejUap9Hgedrbua/4FYCVO7MIamvFafzzn+HL674EDz44Yzd7Ir29ohPPPRdZLT/+cbmIzjxz2UO3227sZXvB5DXuf94v7TZ21WX8eyslBXH+8AfYmzwJrrkGvv51bvzMCH//9/Da18KFx34gc7ZAy4iFaGuDVErR7t+cV6JxqHoN/f1qumgsLpYqwamU/OLLWDAvvlhq10wLUZ2rGM7998umeOtWiQu6915uv13C1i48tU8OA7ItOgZ9smJ6yKk6PCTOt2udxpNOkgObZb6HFkswKGmTk4GQvGe9ttFJJOhIyS511vDUNWuW1driiivgv/7LyegQzjtP3Dw792KR2O02nPDU4eGMicZgEAYmrGq7XgxRjUbpoYGGusnlps17Hvut6rTdsBPSvYLWIhonQygly18h4vOJW+44jV67l2YIIxrzifZ27i15BTt2LO3Cfu1rxf341EMv43DTi6Q2/DwXhL2m7t6NuFePPAJf+9r0098l0tQENZWT7GNbwVRQPXC8jPXqKKWB8qx8/ze8Qfaj3/se8IlP8G+Jd/LBT1XzutfBj7+boOiJR1eUz2jjVFAN51GvxqEhni8XIXdCypS9e11iaKpNfb382RcUjVqL02hXHrjwQvSex/jNr1K87GVQ1mOXUM2y02g7VV4SjbEwRSo53Z1yE36/JDnaBViyhF1MZbDces96aA4BiMfpmJS4xlmdxmU2uJ01RPWssyRMda4Q1aefnupVlMbx40yNL5XKqGisq4OBUauNlRdFYyxGN400hjzmcGcQuwp1fz/e7NUYi4HWdI0FCYVWfMbsaRobTXiqEY15xPih4zw8esai8hnTUUo0n1KKd7X+Fn3oMFx33Zw5FA8/LJF5u0r/G66/Xlbgq69e0diVgm2bJkQ0ForT2BtgS1n2ym83NUne2/e/D1/8+Un8nf4SV/j/kx99pYfiv+yR6oOZFI3Vp+eVaDxYIvb3CaLR3r0uUzSCHNL8+c9ph87hsBxj/vd/T33Svn2yyU8Tjc/obRw+4pvKZ4TVE41eCk8dbWJ9zaC7I6d+/WspY51FnF6bJVZCjteERyJB53g9xcXT0xgJBOTof5micfNmiRCeFqJaUSFxq7OJxrExaXr81ree8JLtNLa0IIWqtM6o0xhJWE18vTZ34ISnFmo+I8j5UCCQ5jQeOeKt/FSr+FpXonZ6aGoB4ohGE55qyAcefb6eeLJs0fmM6axfD5//PNzxpyBv3vkEEz/9xZwbmkcegTNemKLsujfKqvaNbyy7ZUM6209RheU0DjewpTa7v+u110r+3Mc+Bn998TD/kbqK4i//65RdfM45K/4ZDQ3Sa/NA8fb8Eo0+UcMn7EtX6DSCiEaQgjgOMyuo2vmMtmh80Yv4jf8ygFUVjYODoENh77hUk5McSq5jQ91wrkcyP6sQr+eIRr/lzHllDkE21vE4HaN1NDXN6Dfs88GHPwxvfOOyv/0VV0gV4mnRguefL3GrMxuw33KLFHx77DE5bEujo0OG09jI1EYyk07jiGXteFE0WoVwGpsLNDbVoq7OEo3r1kluqpfqNoyMANAZrc5GO2BPYZxGIxrzh1iM+4aluMK0PjpL4L3vhc98Br7/+KlcGvoDI+//hDSgtojHZZ1+5BF4sXoQ/vIX+M53VhSWms62F5RwnLUMH8n/i7G/HyKTNbSFs3ta9apXwcknw5veBD+8rYaiN1wplVRvu03yqjIwd0qJfto/0Sobq0QiAyPPMUNDHExuJBSSFhnTsFfOFVS93LZN3I4TQlSffnqqWMkDD4hdbFu55eX8pvJKTi/fJ/lTR45IIZUsJpkEg5K2PFK71juCY2SEw2xgY2Ms1yPJOY5oVFbetJeEx9gYaE1HPDB7mPEXvwgvfemyv/2sIarnnSeVwPfsmXpuchL++Z8lvGZ0FJ55Ztr3OX5cLlO/n6yIxtExHwnKvCU0LPSI5DQ2tmS+j6yXcESjnX/upRBVSzR2jVQUvNPY1CSiUdfUyt/Fa4XFMoARjflCezv38RJesD6ybB2glBTavPlmuDtyBhdyD92vfRcMD3PPPdLK6oYb4G2XdvMPf3y1VFqxLZMMsG27vB2fPeDmmLLMYBec3bIuuwKruFjMq1tusfq/f+ITshn7wx8yEppq09YGB4Y9XFJ8JsPDHBxfO3sLuC1b5I9pV29aBkrJpXPPPU70j4jGWEyqc2gtRXAuuMBxpPr74ZGRHVyS+KnEjNrtNrLoWNn5OJGqdRKe6oGwqkTPCF00s6F5PNdDyTmOaExZIsYrwh+cw6fOWHVWclO3bIHTTpN+tg72PTE9RPXWW+H55+Fzn5P/pwtKxGmcVjkVMhqeChAh6C3BbzHUP8k4pTQ05/+aPh/19Wk5jeCtNTIaRQNdg2UFLxobG+VMaaisUdZCS1AXEkY05gljB47yMOfykrNWLkLe+la47TbFM74d7D78f3lzy+956UvBd7Sde1rewLfvaaN6fRBuvDEDI5/CabvRnp3CMG7iwD6r3cam7G/Cp2mKk6xKqrDi/ozptLXBob4qJvHnR4jq0BAHY02zi8ZrrhFHcIUNjS+9VPT7XXdZT6QXwzl8WCyMtDLId9wBKe3jEn4tLmSWezTCjEIqExOeWCSPPCv3wA3rJhf4zPzHER2j5XLQ4SXhYbWY6BiuylpY3OtfLzn6djEbwmFZiGzRmEpJX6qTT4YPflDCDmYRjU7l1Cw4jQAD5Wu9NXcW3X0iFgug9/u8OE6jPaFeCm0cGWGQAOMTPiMa7V6NWB94aR4zhBGNecKjD46SoIILX1mSke/3qlfBvff7Ga5eww/jr+EjbT/nyUv+gQtfnJJkkNtumyVub2Vs3gxFapK9PZlvQeE29v8ljo8km7bmoBTZpz8tHeZf9aqMfcu2NphM+jjCeu+LRq0ZH4xzNBqcXTQWFWWkIfv558ve8le/sp445RR5fOqpE/MZkfzHhgbNrtKn4N57V1U0RoqtShYeKIZzaL+IxQ0bCjuPCtLmb1CJ3eExp3GUUgZiZVmrgnvFFfI4LUT1/PNFSaZScPvtcj1+7GMSf3rGGfDoo9O+x/Hj2XMabY0RqWn1pGjsGZCw1EIuhANporHaap/igcM3h5ERuhC1aESjPHYnrXC+AiyGU9iB5nnEvX+qQJHigsuCGfueZ58Nf9lXxsgIbN36WuC1Gfves1FcDG3V3ewbzP8704F9k6znCKVrc9D0aONGsa0yiFNB1b+NTV4XjfE47am1pPDNLhozRHExXHaZtER57jl4+9truGLtSVQ89RQcOCA7jZNPBiSt6o474DWvUfjaz4G775bdahZ7NMKM8DjwxGbn8CFx7ze2FXZIHEgLw7KytAq4XhIe8TidiMWYLdG4daukXfzsZ/C+91lPnnee5Oo//bRUh9uwAa68Ul7btQu+/GUJESgtZWxM/qTO+J56SsSlYz2uDPv6G6hcB/0ntvtwO92DUvnVOI1yDaYqqsSpcXISPEA0akSjhSMaJ6zTnAIUjcZpzBPue66Z00r2UhfO7EappUUW1tViW8MA+xKtnsidWgn7n/fRxoG8WU0d0Rg80/tO49AQBxG1mE3RCNLq5oYbxAB685uhpesx3nPnpey/67A4HlbJyEcekUiYSy4BLrxwqmDOajmNk945IT981E8x4zRvyv8w98XgtE1xEqs8QppozGbVxte/XqJR7dYZTu/Mz31Oyqt+5CNWQjgiGicmnCrHnZ3ytKMR77pLTlttR2mFOOGpZS3emjuLnmERjYXuNNbXy5ZmcLRMDhW8JBqN0+hgb9e6ElYkgQlPNXiRsTF4pHcLF4afzvVQVsy2LSn26zaSTzyZ66FklQPHy9nC/rwRjc3NUF4OB8pPhUOHcj2clZEmGpfZBm7RVFfD3/2dtGS87z645KTnuLn/crYfvZN39/6j07L0N78RZ/LlL4dpPXVWSzSOWw3GPbDZOdxRQivt+AKZDZ/3KtNEo8fCUzsQCy9bTiOIiejzScT+gQNIJEZLixTAaWyUvkU2u3bJo5XXaOdCtrQg8Yd79lgXaWaY1mfTg6Kxe6QSRSpTBdY9iyP+I0r6U3ng8M3BiEaH+nq5V3THrUMh4zQavMif/gSjqVJeclLHwp/sctZdsJFJiun90d25HkrW6O+HSKw0r5xGpawKqqotb5zG8tLkqvWlUkpq3vzwo0/TTivv4Ft860+n0dYmbXBuu01er64GzjxTGpFD1sNTq6vlYDwyZv08D4jGQ90VbOBwxtwer+OIRjtGzivE46siGk86SUK/OzpEE97+WzXlNn7wgxLfa7Nxo/xBLdFou5MtLUgpZK3hFa/I2NhqamSTOuD3WGixRU+iivqSEceoLVQc0TiAiEYP3EcdolG6/GspLZ2qpl2o+P1SK6t72IpiMaLR4EXuvTsp+Yy74rkeyopp3iruQMevH8vxSLKH026j9ChUVuZ2MBmkrQ0OJNZIIyMv92q0ROOmltHV6L8+nR07aKSHr1d9lGeeTPLKV8KnPiU5j5dcYn1OSclU5dssO41KyUYhkrA2zh7Y7BweqGYjh2RzZpgSjdXVnpg/h0SCTpopLkpRX5/dH/Wyl8Fjj0lkwaWXwmf4JKntp8A73zn9E5USZTnDaVyzBglNramBs87K2Lh8Ppm/AeolFC6ZzNj3Xg26E7U0lg/nehg5Z5porK72nNPYWbSOpqasdnfyDI2N0D1oFZw04akGL3LfXeOczhMEtnrftbJPlDufHfJWL6MlcOCAPG4J59cNp60NDkbqSOKTXoNexRKNm1tzsEHbtk12iueey0knF/Gzn0k+43veA298Y9rnveUt8Fd/lfEKxrMRDEIkZi2SLt/sxOPQE6uitaTLyQctdBzRaDscXskXt5zG5obkqmxWN2yQoqlveAN86tYdvG7rUyQrZ7m+du2SnMZEgo4OKC2FYEDD738voeMZttWCQavPptbecoqBnokADRUeOqjIEvahR38/3nMaR0boUs0FH5pq09gI3b1+iUAwTqPBa4yOwh8eK+VC7oXW1lwPZ8XY4YCdNKf1Isgv9u8HH0k2rp3I9VAySlsbjE/6OcZaT4eo6qFhnmcTm9tycKxaXi7W4gc/6Dx1zjlw001Tp9WAJGL99rerMqRAACJRqzWMyzc79p46XBHL7UBcxDTRmErJouEFLNHY0rx6Ire8HG65Bf7lX+CXv4SvfnWWTzrzTCln/OSTdHTIQad6/qDc8zKYz2hTVwcDdiEqj4Wodk/W01jt4aiTDOH58FQajWi0aGyUYCpqa41oNHiPp56CsQkf5/CHvBCN9o2pI3SarNp5yIEDsL64k9Lm/OpHuWWLPB7A23mNXccmSVDB5m05SsS5/vqM5kWtlGAQIkM+qcTj8s2OPbyqilRuB+IigkEYHoZkhSU8XD6HDlZ4anPz6h7eKAUf+pCEqX7843Dw4IxPSCuGc/x4WmgqZEU0BoNpOcUDAxn//llDa7pTYRprjWi0cwG9Gp7alQwb0Whhi0ZdU2vCUw3ew44C3MTzWc9vWg1KSqSdWOfaM+H++z0XjrMY9u8nr4rg2DhtN3xbPV1B9WC7iMXN20tzPBJ3EAxaa6MHTshjlsGYR6nCK8auwDnosw6pXD6HDrbTuHb1tylKwTe+Ieck1103I6J37VrpIbFnj+M0ctddcmhrn5xlkLo6GIhbOcUechoTg2OMUENDML8iapZDUZEYU150GieG4vRN1BrRaNHYKMEaIzVrjNNo8B62aGwNJ6ZXefMwzc3QUX2ShACtUgjeaqE17N+v2TKxN+9E45o1kt9zoOaF3haNHXIdbWozt0eYEd7o8hNyx2msNhUbbJy2DdqyO1w+hzaJ4Qki1OVENILcz264Ae69F26+Oe2FtGI4HR3Q0pSSyqkvf3lWKoXU1cHAiBUe7iHR2HNYCvM11nureE+2cNqkeqwgVe9QCRqfEY0W4bA89pWtNU6jwXu0t0OVP05wQ22uh5IxWlqgczQosaq33Zbr4WSUgQEYHFRs4bm8E40+H2zeDAdKTpZynx7lYHc1PpJs2JDrkbgDWzTqSvefkDtOY40/twNxEY5oTFlrhMvn0KarTxz/5pbcHQC87W1S2+ZDH4Jjx6aeT5z2Ir5iKot6AAAgAElEQVTw9KVEo7A2dUQchyyEpoLl9A/7SKG8JRqPjgHQEDKh4mCJf9tp9MjBDUDXsIRGG9Eo2D1H+0qN02jwIO3t0Oo/htrg/XxGm+Zm6OhQklTyu9/B2Fiuh5Qx7BLtazmWd6IRrLYbqY2wd684xR7k4ECAdcVdlJTkeiTuIBiEiQmIV4ZdLzgcpzFQ4I3h0nBEY9KqBOryObTp6Jfw8Gz2aFwIpeA735H3/7veJR0vvvc9OOk7H+If9Oe59NwBrq28VT7xpS/Nyhjq6kBrxZCvzlOisfvoOACNTcb1hxmiMRaTolQeoCsqrYuMaBQcp7G4yYhGg/dob9e0Th7MiyI4Ni0tkmicevXlssG5555cDylj2Gt+mN68FY0Hh8OkxiemGlJ6jIPDYTZXdOZ6GK7BER2lTa4XHI5oDBbndiAuwpm/Catvpcvn0KYjIg20cykaQaInPvc5+M1v5ONrr4XmtX7u48X86oofUPfwr+GMM8hWM0m78mYksNFTorGnU8JSG5rMNhPSRGO1VZAq5oEKz1rTmZCwdiMaBcdpVA0mPNXgPdoPa1pTh/JKNDY3i0nV94KLpKJFHoWo9vXJY4i+vBWNifEiaZny3/+d6+Esi4PxZjbX9OV6GK7BER0lja4Pq4pFpWJJZdDYxDbO/I1bFTg9Iho7h2S8dhumXPL+98MFF0hBk1tvhT89XsKLWw5IwuMf/5i10FSYmr+B6lZPicbuLrkWG9aYAxwQ0ej0aQRvXIejo3TpBsCIRhtbNPbqECQSEoZQQBjR6GFGRiAy6KOVdti0KdfDyRj2yXLHQJk0MP/VrzwTyrEQtmispz9vRSNYFVQ9KBqHh6FvMsjmuvyr2rtcHNFR5IHw1AEJiasK5UdRsEzgzF9CnDu3z6FNR7SaYjWRLQNvSfj9og/374crrrDq3ezaJWvT5GRWRaPT469ynadEY08PVDFCRagi10NxBfX1khueqvCQaBwZoYsmAuWj+VJnccXU1MjhUV/SurEWWIiqEY0e5sgReWylHU4+ObeDySD2yXJnJ3DZZfLBo4/mdEyZwhGNZfGpE8c8whGNDbs9KRqff14eNzV4YEFfJRzR4at3/UYnNjiOIkVZwOxwbMrLpbB2JG61kHG5W2zTEa2lpaQvGwVJl4XPN6M46q5dUg67ogJ2787az3Wuv7JmT4nG7n4/jXSb/jcWkpsKQ37rFMAL12E0ShdNNAVGcz0S16CUuI19E1ZhsQILUTWi0cPY7TbWl/bA+vW5HUwGsUVjRwdw8cVyzPvLX+Z0TJmivx9qiuOUNNdnpTx7rlm3TnqbHQic4UnRaDfy3twcz+1AXITdmDqi6lwvGqODk1QRRdVU53ooriIYhMhIkdxzXD6HNp2JAM1lLnb8d+2SxwsukF5DWcJxGkuaPCUaewaKRTTm4eHocnDmMWXdUL1wHVpOY1NdYYVgLkQoBH2j1vvaOI0Gr+D0aNxaJsegecI0p7GuDnbuhMcfz+mYMkVfH4SKBvMyNBUkbGPjRtjv2yq2nReS/dM4uE8Wx82t3qz8mg2c5vAEXF/1LzqUpIqo2ajOIBiEyKDyVGPxjrF6WipcvCE780yxcF/96qz+GCen0R/2lGjsHiqlgR7jNFo4ojHpodY3tmgMm/UwnVAI+uJW2LURjQav0N4OxYzTfFpDroeSUUpL5Qbb0WE9UV+fNxdmX1/+5jParFsHxyetrPmnn87tYJbIwWcnqKeP2kYT3mhTWysGldOywcUHAbGRFJXEjGicgd1r00uNxTsmQrRUD+d6GHMTCsnB2DvekdUfU1YmIcYRVQejo1J8wwP0DJeZ8NQ07Nzc/jHr3uSl8NRGneuRuIpwGPqiVnSBCU81eIX2/eOs4yi+HfmTz2jT0mI5jSDxcXlyYfb1QSjZndeiMRyGPnth9FiI6sEDms0cFKVkACSIobYWIpNWyKeLRUd0RBuncRYc0egRpzGRgMFULc3V7j2gACQsZhWifOrq0sIaPeA2JpPixDT4+jENbwXHaRyzRLQHrsNob5wo1TQ1G6mQTigEfUNWVeA8MTQWi3kneJj250bzrgiOTXNzforG/n5NaLwz70Vj72CxFIjwmGjs7lG00GFE4wyCQW/0+YvFME7jLHhNNNr3/pagyS0Ga/4mrfe0B0RjXx+ktI/G0vxYtzOBIxpHvdP6puuY9NpsWuvP8UjcRSgE/REfSXxGNBq8Q/sxf96KxpaWtPDU2tq8EY19vZoQvXkvGoeGFOPbT/OcaIzGFNWMGNE4g2AQImPub9kQjfmM0zgLXhON9r2/JWiqNoLlNI5aDpUHRGNPjzw2VLj/vbZaOLmpMct59UB4aleXPDatz16hJy8SCoHWigjBvNmbLhYjGj3K+Dh0DpbTWtQBGzbkejgZp7lZblipFOI0jo1JPoeHGR2VTW2IvrzulGs3v+1vOxueeiq3g1ki0bhPnCojGqcRDEIkYeV5unizE00Y0TgbwaAciCcra1w9fzadx6XYUnPIVG0ESzTaLVM8IBq7u+WxsdKIRpuiIllW+geLJGTXA4c3XT0iEZo2lud4JO7C3uP0VbQap9HgDY4dA42P1jUTeVU51aa5GSYmrPXRrvnv8YvTXuvr6Z8qEZuHhMPy2LvuhXLkbB87e4Bowi+iw4jGaQSDEIlZm1YXb3Zio34TnjoLTgXckgZXz59NR7uIxZYGU7URrOsvajlUHhCNjtNY7Y2iPatFXR0MDCAFqTxweNPVVwRA07riHI/EXTiisbLVOI0Gb+C029iSn2EDLS3y2NnJlGj0+MXZ1yeP+e40OqIxbIVNeyRENZmE0YkiIxpnQTatsoFws+iIjhVTpeKm+MYMnAbxxR4RjceSlDBGXX3+9bJdDnV1MDBkbdc8IBodpzEwltuBuAxHNHokTLwrUoqfSUckGQR7j9NXttbzZsZSMaLRo7TvlQIB608L5ngk2cE24jo6yBvRaK/1Ifry2mm0F5je2s3ygUdEo91JooqonAQbHJzm8ODqzU5svJjKkgnpEWJwcESjP+Tq+bPpOKZpphNVWZHrobiCujpIJBSj5UFPiMaeHihWEwRqTauGdKY5jR64DruGymnw9+M3dXCm4TiNJS1GNBq8QfsTsnCs270uxyPJDtOcRtv18fjF6TiNVWPSeCtPcU7hJgLyH4+IRnsNryqZkAQUg4OkFStGKXVtWNXkJIwmS6gqHc/1UFyHIxp99fJG1+7ezHd2IlWM8/g+uRSc+QtstFSHu+nthbBvAFVtwsTTqa+3NH9VlWvvo+l0jVTSVOz+Q4rVxu652etv8ryZsVSMaPQo7XsTNNNB6Wnbcj2UrGAbcfkYnlrflN/5AfX1YvT09gI7dnhPNFakcjsQF+JsWgm69oTccYrLTB7cTKbmLyBx2GPuDhvs6PaJaKwwTiOktWsoX+MJsTEyAtVqBCorcz0UV+G58NR4DU1l3t53ZYOKCvnX52vwvJmxVIxo9CjtRxSt6mheVk4FKCuTjU4+hac6onFNWW4HkmX8flkce3uBU0+Fp5+2yuC6G3sNr6wyoY0zcURHkXtz4mzRWFnu/vfaauPMX8qK2nC58OjoLaaZTiMaLZz5K2t2/dwBxONQmTJVjGdSVyetb1JVNa69j6bTNRagqWI418NwJaEQ9KXqjGjMFkqpHyqlOpVSw0qp55RSb7Oef5FS6i6l1IBSqlcp9VOlVHPa1/2jUmpCKRVN+7cp7fWdSqnHlFJx63Hnav1OuaS9v5LW2kHyOdi8uTm/nMb+fqj1DVPcEs71ULJOKJQmGuNxOHQo10NaEMdprDaicSbOprW8xbWbnSmn2N2hl7nAmb/JGvnApXMIcrsYihaZ8NQ0HKexuNETojEW01QY0XgCdXVyfjpcGnb9PKZS0D0epKkqluuhuJJQCPqSAdmXujzcP5OsptP4BWCD1roGeDXwOaXUGUAQ+DawAWgFRoDvzvjan2itq9L+PQ+glCoBbgN+aH2fW4DbrOfzllQKjsbraW3J79yd5mbLaayokBwzj4vGvj5NSPfmdREcm3DYclZPPVWe8ECIqhPeWGMCMGYy5XQ0uXaz4ziNJiLuBMrLobQUIhPWJt7ForGzUx5NeOoUjmgsaoBh9zs/8Zimkqi5GGdg58L1+90bsWHT3w+TFNNUa9qmzEYoBH3jNZJMnyicv9Gq7Y601k9rre1ECm3926y1/p3W+qda62GtdRz4GnDuIr/tS4Ai4Mta6zGt9VcBBVyU4eG7iq79I4xTSmtbXmtjWlqsDYRSUgzH42EAfV3JghKNvb3AKafIEx4QjY5TZUTjCUy1bGh07WbHmT9jbsxKMAiRcUuEuXQOwTooBAlPNU4jkHb9qTrXHtqkExtJUUHcXIwzcMS/3/1OY1eXPDYF3Z3/nCvCYehLWIciHt+bLoVV3R0ppf5dKRUH9gGdwG9n+bQLgKdnPHepFb76tFLqXWnPnwI8qfU0b/hJ6/mZP/vtSqk9Sqk9vb29K/tFcsyRh44A0PqC/O4lZ4enao2EqHrdaeyapJ7+whKNVVWwcaMRjR5nKqcx7FrBYeZvfoJBiIxaIsylcwhTm1WT0zhFba2cnQ6oOg85jTHjNM7AEY3USTGqiYncDmgeHNEYMoXFZiMUgr6YdT/1+N50Kazq6qq1/l9ANXA+8HNg2hGGUuoFwPXAh9OevhXYDoSB64DrlVJXWa9VATMl/pD1M2b+7G9rrXdprXeFw97OKWvfI6K39UX5LT5aWmB83Ko2lg+isT//ezTahEIS3pJKISGqTz2V6yEtiCM6AqbdxkzstGI39/lzwlNr8jfPeyUEgxCJl8p/XDqHMKWJahkyotHC55NrMJIKiEPl8hyqWEwZp3EWpolGmLppuZCuYyIWmxuSOR6JOwmFYDhRwhglxmnMJlrrpNb6IWAt4LiGSqk24HfA+7XWD6Z9/jNa6w7r6x4BvgK83no5CtTM+BE1SF5k3tL+jNxo1u9em+ORZJcT2m54XDT2D/pFNDY15XooWScclsr+g4OIaHzuOdeX+XdEYzC/W6IsB78famrcHR4XHZGNdFWtEY2zEQxCJGqlNLhYNDrin5gJT02jrg4GJmvkJM7lOVSxhDJO4yzYh29DKcvXcOm9FKCrXdbrpmZTGG42QiF57KfeiMZVogjYDKCUagXuBj6rtf7BAl+nkbxFkDDWFyil0t/VL+DE8Na8ov2wJuAfpiaY35ujlhZ5dNpueFg0JhIQGysuGKfRNvOdCqrJJOzdm9MxLUR0KImPJKUBs1GdjUAAIjrgWsERG5RQr8pgfud6L5dgECIjlovu4s2qEY2zU1cHA+OWc+fiEFWtIT7qk/kzTuM0aq2MosGkJRpdei8FcRoriFFVX5rrobgSWzT2EfL03nSprIpoVEo1KKWuVEpVKaX8SqlXAlcB9yil1gD3AF/XWn9zlq+9TCkVVMJZwPuQiqkA9wFJ4H1KqVKl1Hus5+/J+i+VQ9p7y2mtjuR6GFlnmtPo8UI4/f3yWF80PHXcmMecIBrB9XmNscFxqoiiqs1GZzaCQRhMube/WHRAqkmbTc7sBIMwOGIt+S6dQxDR6FMpSot1XreUWirBIETGrHBdF4v+sTFIpUx46myUlUFJCQxOWg6si6/Drk5NE12omhOyvQzMEI0e3psuldVyGjUSinoMiAA3AB/QWt8GvA3YBHwqvRdj2tdeCRxAQk6/D/yz1voWAK31OHA58CZgEHgLcLn1fH4SjdKeaKC1yd2hfpnAFo354DT29cljKJiUigZ5jnND7QPWrZP/dHfnbDyLITo4SRWmt9hcBIMQSVa7dqMTjUygSFEeLMv1UFxJICB7mxQ+184hiGisLBpHVZp8xnTq6mAgYb23XSwa43F5NOGpJ+IUgh93v/jv7FI00QXVRjTOhn0wXmiicd6KD0qpHyCCb1601m9a4PVe4MVzvPZp4NPzfO1Vc71mvf4EcMZCY8wX9DN7aWcrF272dgXYxVBRITfYzk4gHJDdxMQEFHsv58x2GkMNhVHZcZrTWOn+U1WA6FDKiMZ5CAZh/3il7AqTSde5QLGhSSqJGad4DgIB0FoxUtlErYuvRRGNo6YIzgyCQRiIWi66i8NT7fBi4zTOTiAAg6OW+HfxddjV52c7XVDVmOuhuBLnYFw1eNrQWCoL7WAPAAetf0OIq+dHHEMfcBni8BlWicE9BxihhtYdM+v/5Cd2242pDHJvnug4TmNTYVTmtG+ovb1I6b/KSlcvkADRESMa52NaeJwLq/5Fh5Nm/ubBvoUOVrS4+lqMxaDSP2byGWdQVweDsSJSKFc7VMZpnJ9AAAYTlvh38Tz2DxVJDQbjNM6KXQm3t2ytZ/ely2HeHazlAgKglLoTeFV6ZVOl1HnAJ7M3PMNM2v8kzXNaT6/L8UhWh5aWtPBUkBMdW5F4CEc0riuMjVB5uewXnJaoVVWuXiABoiMY0TEPwSBEEmkn5DXuOriKjWhTfGMe7F6bg+XNtLpdNPoSxmmcQV2d5AoOU0PAOI2epbYWhiJWtJSLr8Nowk81I0Y0zkFxsWxL+1LNMOj+lmKZYimxci8C/jjjuT8B52RuOIaFOPKMbLxbN7krNCxbOE6jXXbMoyc6fV1S2bFug7s22tkkHJ4Sy1RVuXqBBIjGlBEd8xAMQny8mHGKXTmX0ag2on8enF6bJY2uPsAR0Rg3TuMMbNEfIejq+XOcRv+YVH0xTCMQgMGotX9z4X0UJPsgPl5s1sMFCIWgz9fo2X3pcliKaHwC+LxSqhzAevwn4M/ZGJhhdtoPy2Nra06HsWrYTqOuTXMaPUjf0QQBIhStzf8ejTbh8Ayn0aULpE0soYzomAe3b1qjMTN/8+EEaxSHXX0txmJQSdw4jTOY1hjehdefjeM0li9YDqMgCQRgcNjaert0Hm3hX0XUOI3zEApBnyqsQjhLEY1vBs4FhpRS3UiO43lI5VLDKtE+WEuZf8IpNJLvNDdLCe9Bf7084VHR2N8xXjA9Gm2micZq91bdtIkm/EZ0zMM00ejCuYzFjVM8H45oLAq5cv5sRDRGjWicwZRorHd1IRzHaaxI5XYgLkW6hyl5f7v0OrSHVaXi0ifEMCuhEPSl6jy7L10OixaNWuvDWuvdQBvwaqBNa71ba304W4MzzCAWo32yhfXB4ULo2gCktd0YtVZMj16cfT1JEY1NheM0hkLechqjo0VGNM6D20WjEf3z44hGX50r588mFoNKHTXhqTNwrr/yFtc6VJDmNFYWRqXwpRIIiLCeqHLnfRSm5rCqbLIgWoQtl3AY+ia83UN8qSz5qtZaHwH+CzimlPIppcydYbXo6aGdVlobR3M9klWjpUUeO2NWLqBXReOAj3r6C85pnJbT6OKNjtYQHSsW0WEq/s2KIzoIuHKzExsrEqfRiI1Zqa2V/d+gcu9mFWTDWpE0TuNMHKextMkbTmOlCU+dDac8Q0Wza9dEx2k0bvG8hELQN1aNHjSi8QSUUi1KqV8opfqBSWAi7Z9hNejp4RhrWddSOBeyrbE6B8tlx+PRE52+oWJC9ENDQ66HsmqEw5BIWKeWLncax8dhMuWnqmjMdf0H3YLrcxrHiqkqHjcn43Pg80nB24h2p+i3icWgMjVsROMMnOuvuMGV15+N4zRWmfvobDiHb2VNrr0OjWhcHKEQjCZLiA0nIVUYf6uluITfAsaBlwJR4IXAr4B3ZmFchllIdXbTQwNNawuj1x+khad2+eSIzqNOY3+8nFBFvKAEiZ1329uL60Wjs0iWmjOwuXB9eOp4CZUlZv7mIxCAwZSVX6zd5wRpbYnGyWHjGM+gvFzSywb87haNjtNYbYLQZsMRjaWNrryPQtp6aCL958Xu/tZHvauvyUyylKt6N/AWrfWfAa21/gvwVuDvsjIywwn0HxomSRFNraW5HsqqUVUlNVQ6O7F2PN4TjfE4xCdLCdUW1obWuaH24fpCOPbpeGV5YZwWLgc3i8ZkUk58jeifn0AABierYHJSKoy5jLExObCvnBw0TuMsBIMwoNxdCCcWgyImKK4qnH3KUnDCU0vCrhUajmisNlEb8zElGgungupSRGMSCUsFGFRKhYEYsCbjozLMSvchOcJr3FxYxz922w2visb+fnkM1bvvZD+bnOA0TkxIHKgLcRbJ8mRuB+Jiiosl3TPic1/1zWmFGwxzEgjA4LiVs+uyOYS0w5vUiHEaZyEQgCEVcK3YADkkrVQJkxs+B16oYmwPq7KmcCKjlsM00ejBvelyWIpo/BNwsfXxncBPgJ8DezI9KMPsdB2VU/Sm9YXVMLexEXp68KxotIvB1DcU1g34BNEIrt3sOKLRFG+Yl2AQIsXuOyF3xIbJwZmXYBAGxywx5sINqzOPxIzTOAsSXlzjeqexQsWNaJyDaVWMXXYftXHWw9rC2rMsFXuPY5zG2XkjcL/18QeAe4GngKszPSjD7HR3yoaosTHHA1llwmFLNNZ6s7RxX7e4V6E1hRWuY5/CTRONLtyoghGNiyUYdKfTOFW4wczffAQCEElYfddcNodgRONCBAIwmKx2rdiAtJYpRjTOihOeqtxbkMqJ3DCicV4KMTx10RVVtNaDaR8ngM9mZUSGOenqk+kqoFZ/QFqT+LO86TT2Hx4BAoRaC2sRra2VkMa+PmCdR0RjjSneMB/BIESU+/r8OeFUhRW5v2QCARiMW5EqLptDmCEaTXjqCQQCsH+yQkSj1q6sFByPaxGNRvTPSnW11fpG104VpHLZPEajoEhRHizL9VBcTW0t+P2a3mTYk3vT5bCUlhvFSqlPK6UOKaVGlVLPW/8vrFjJHNI1WEqpb5yamlyPZHVpaJC8wGRN0JMXZt9h2ZyFNhXWxCklJ3G9vchKCa7cqIIRjYslGISIC/s0OifjVe7afLmNQABGEkVM4nfdHIJxGheithYGxyqkkNGoO/s1x4ZTVGDCU+fCZxeCT9W4tiBVdDhFFVFUtTmFmw+fD+qDuqCcxqXskP4FeBnwDuA0pNXGRcA/Z2FchlnojlbSVDHitkOprBMOy2Fcf2mL5HIkvVWspO9oAoDg5rocj2T1cVxil+c0mnCcxREMWpsdl82jEf2Lw86nGsZ9cwjGaVyIQAAGR0vR4Mr5A4hHUzJ/RjTOSW0tDCXdW5AqOjhJFVHTc2MRhMKmEM5cXAG8Wmv9e631s1rr3wOvAf5ndoZmmMbkJF1jQZpqE7keyarjFFTxWcmcLi4CMBt9XRMEGaBoXXOuh7LqOE6jR3IaKwPFuR2IywkEIDLpvvYpsajkMlbWFk4P2+XgFOFwoVsMxmlciEAAJlN+EpS7dh2MRbVxGhfA7VWMo0NGNC6WUNhHn2owTuMszOVvFZjvlSP6+uimkca6wutD1tAgj71Y6tFjF2d/ryZEHzQXnmgMh62cRreLxiFxryuDJtp+PoJBGJmsYHLEXYdX0UFptVEVMKJxPuxem0Y0ehO7iMog7m27EY9rM38LUFsLQ+OWk+7CebTDU41oXJhQCPp8RjTOxk+BXyulXqmU2q6U+h/AL63nDdmmu5summhqKrzqgLbT2JOslw88FgbQF/ET8g9CWeEllTvhqW7PaYxMUMooxbVmozMfjugYcVcYb3RA8oKMUzw/ttMYIejKa9GEp87PNKfYhWIDIBZXxmlcADvMGHDldRgdtoS/EY0LEg5DH/We25cul6WIxo8AdwNfBx4DbkLabnw4C+MyzCDZ2UMfIRpbCu8k3QlPnbBXTG9dnH0jpYTK3bcwrAZhq6jYRKnLnUaTw7EobNEYibpLnMUiEoFRVV9YbW2WiglP9Tb2/A1R69rw1HhCmZzGBZhWxdiF4j8W02Y9XCShEPQnA6QG3Xk9Zpp5FYhS6qIZT91n/VOAbXmdB9yT6YEZptN7cJgUfppaC29TVF8vlTh7Ry23ymuiMVHBzrrxXA8jJ9h9jPoTFTSBKxdIkPBUs0gujCMax8ql8l+ROw6xooMTpkT8InBEY2mTq0VjBXEKrkz4IvBCeGps1G+cxgWorYWhmHXvdOF1GI0pWolC1fpcD8X1hEKQpIjB3gkKodThQiv+/57jeVsw2uJxU8ZGZJiVrufjADRuLrxNbVER1NVBT8xahLwmGidqCQUncz2MnOC4xP0+miorXblAAsRGjGhcDI5oJCg7fHsXm2NiQ0kqiOOrMfM3H45oLAlDtDO3g5mFWAzKiyfwTWgjGmdhmlPsQqdxYgImJn3GKV6AQACGon5SKHwuXBOjcZ9ZDxeJfTDe15MyolFrvXG1BmKYn+6j4lQ1bSrMG3E4DL0jlovgoYTjeEwzqssIhQqzXpQjGu0Kqi5cIAGiI5gcjkUwTTRGo64RjaZww+KorpbeYoNFYRh5LtfDOYFYDCqLxkEXFWQO+EJMC091odMYl7Nt4zQuQCAAWitGqKbWhfMYTRSZ++kicURjH5yU26GsCqaplUfo6hRzt7GpMMVHQwP0Dlp5VB5yGvuel9PgUJM7wvhWG/uG6hTDcatojGIWyUVwgmh0CdGRlBH9i0Apq22Kv95V82cjonFUXMZCa0i8CNwenmqLRpPTOD/2PA5R68rrMDpmRONicUTjWNVUfH0eY0SjR+julalqasrxQHJEOAw9vUqEh5dE43MDANSvLcxKgLbT6LTdcOECCRCNK7NILoJp1TddtGmNxYzoXyyBAAyqOldei7EYVPpGTWjqHJSXQ3ExDBY3uDI8dVpOqglPnRMnzNiF1+H4OEwk/eZ+ukicPQ4h6OnJ7WBWASMaPUJXpJRKf6Jgr2GndUMg4C3ReFBCaUOthXnqWm91SXHCU10kNNIxORyLo6wMykqSrqu+GY0Z0b9YAgEYdKnDEY9DpYpPtegxTMN2igeLw668l05zGo1onBNHNJY3u24e7dtClS8BJaZv8UI4TqMRjQY30R2toLHcXTeX1aShAfr7IVlb519Vv50AACAASURBVKmcxv4jcvQaagvkeCS5wS5i5PqcxlETjrNYgjVJ14WnxhJW8Q0jNhYkEIDBlDtFYyxmCQ7jNM5JIABD/jp3O43Fk+B3Vy9XN+GEp5Y1uu46dNrelE6aEPFFUFEBZaUpegkb0WhwCVrTlQjQVBvP9UhyRjgMWkN/xTpvOY3Hpel4aFsoxyPJHaGQB3Iax4pFNJo8nAUJ1mrXicZowgqnMu7GggSDMJh05wFOLAaVOmpE4zzU1sKgz13h4TaO01ieyu1AXM5UFeMG182j4zSWJ3M7EI+gFITqUsZpNLiI4WG6dAONwYlcjyRnOFU4y9d7SzR2TaJIEWwt3E1QOOzunMZUCuLjRSYcZ5EE69yX0xgdLabSP2bcjUUQCEBkwp2h4rEYVKaGjWich0AABrU7C+E4TmO5nv8TCxynoFFx2HVroiMaK4zwXyyhsM+IRoOL6O6mm0aaGgv3Im5okMfe4hZvicZ+RdA3hL+ocMM8nHxUl+Y0JhKg8Uk4jmFBgnU+1zmNsfFiqkrGcj0MTxAIwOB4hcyfdtfmPhaDykkjGucjEIChVLWrw1MrK9z1vnIbTniq332FcIxoXDrhRh+9viYjGg3uYKKjl35CNLYU7im67TT2+Ju9JRqHigiVuG9xX02miUYXblSnwnGMaFwMwZDfdaIxOlFCVUnhRmIshUAA4hMljE8qKZXoImIxqJwYNLmp81Bba4UXu/AAzglPrSrcQ9LFUFIikfSDvjrXzaOzHpr0/kXT0AA9vkYjGg3uoOc5EUlNraU5HknucMJTCUshHJcJj7noj5URqkjkehg5JRSS8FRdWQWTk67bqE6JRnOyuhiC9e5yGpNJSCRLjVO8SKY1iHfJHNrEYprKyUHjNM5DIACDE5WuExuQFp5aZbaWC1Fb685r0FkPa8wcLpaGBuhJmfBUg0voOiTHd02bCrdIh9O6IVUvSWguu9HORd9YNfVVhR02Fw7Lxn6wyCoG5LK5M+E4SyMYhCECJIfcMY+2u2EKNywOpwiHy9qmyHmSMtVTFyAQgMRkCeND7juMNE7j4pHcVCMa84GGBoilKoh1ue8gJ9OYd4UH6D4izkzjlsJdSIuKRDj2TNg7Hg+EqGpN/2Qt9YHCdkAclzhlKX+3LpKV3nCvc00wKI9DEXeIbHv+TB7V4rDnz22i0cmHM6JxXpx8uMkKGHPXgWQsBooUpdWmoNhCBALuDDN2rsPaotwOxEM4NTe68v/g0ohGD9DVIZuzprWFfRGHw9A7am0mvCAah4bop576YGFvZh3ROGntVl26SFaZNKpF4YgOl1yCzvwZ0b8obKfRbRVwjWhcHNOcYpcVw4nHoVLFUVWFGxW1WGprYWiyUt74KXccwEHaIVygOLcD8RC2aOwZKHLVXGYDIxo9QFePTFNjY44HkmPCYeiNW4uRW3as85A41k+CCurDhX2Zhayo1L4J64jcRe4GpC2S1YVbaGopOKJjyB3va1O4YWm4NTx1mmg0hXDmZFpOqotEP8gcVhA3/W4XgVPFWGsp4e0SoiOaEsYoqS3P9VA8g70370nVQySS28FkGXes+oZ56Y6UUOOPUl7g13BDA/SMlMl/hoZyO5hF0H9IToHrm4xDDNA7ZrkHLtqogsnhWCq20xgZdofIdsSGyaNaFJ4QjcZpnBOnxx/u69UYj1vzV1GR66G4ntpaGBy1NnUumsfo/2fvTYPjSs/73t/bC9BAA+j9NACCJLiAMyNRmpFmLI0tjeSRUrIVy5IcL7Gi6y0VyU7sxEkqcZaKElVZ9o2v74d7c1N2bJVyJceLZNlxXJJ9rZFtSTMjWxI50gxnKM0Q3AkC6B1Ld2Pp5dwPb3cT5HDp5WxoPr8q1iHR6HNe4qDP+/7f53n+z3qdCcqyC9cD7UhjhuF3UJVV0j5gdTNMesxbaShukEpBbq2VMrEPIo3FK3oiSMyGXB6Ju3QijVut3WcPLVRhj2iM3t/ivls6orHsjfSlzv2LeEPEeh0RjfsbL6enVsom42ZFIo1dEI3C+vYIJnjqc1heE9HYK52WcBgiGgX3yWxNMT1VdXsYrpNKQWHNTwPfvhCNhes65SR+8P6eQMfHIRSCQtV7u6oA5Q1dgzAR84YI8jod0Vj1Rgug8po2mhLjhu4YH4dg0BTRuE/xcnpqtdzQ909E4z2JRmG37mebkKfuY3m9IaKxR8bHYWK8IaJR8ADb26w2kkzHvNXbzg0MA0xTUSCxP0Tjsr5niXmpz0kkoFBpiQwPLVQByqUaiiZjUW+IIK/TEY1b3oigV0raQVIixd2hFEQjpqd6bYLUNHaLpyONm01d0yjpqffkpjRjD30OyxumiMY+MFISaRS8QC5HhjRpQ5wBO7VxoUP7QzRmtf2yiEadoppfb9mwe2iCBKis1whTwTclk2Q3jI3BiL9OaccbRdblgt6cmYiLzX+3RGPKc4tVEY3dMTEBSpnerGmsmBJp7JKbIsZe+hyWRTT2gzHtE9EouM/21SxrxJielVvVEY3jh/eFEU6xoIV+PCEGHYkEFNb9OszhoQkSoLwm6Ti9oBTExrYpNaagVnN7OFTW9BjCcYkUd0s0qljzJzwlOjqiMdTUjXmF2+LzQWTKm+mplbK4p3bLTRFjD93HckU2bvrBSCuy/lkRjYK7ZBa1OEofkl30Ti+cscP7I9K45mdMbd33rrfQEo0FpRcTXhONG606HBGNXRMb39Hpje2Vvou0axrH495Il90PRKOw5ot76rPYEY1TYmh0L6Ixb6anVreQSGOXtNNTvRZpLFd8sonaB+k0ZJVEGgWXyVzUBjjTR+Uh3Ik0jszuD9G4ESQR9M4Oopto0YieiDy0qwpSw9EPsYm6Z9Iby+sNxiW9uCeiUe/VUnVEoxga3ZNIxHuRYoBKVUlNY5d41cW4vCWisR8MA3KNOM1Mzu2h2IqIRo+zekWbPKRPRFweifskEvqY88/sD9FYDZEIuR+J8QKJBBSL0AxPemqCBChLDUfPxKbqOtLogUVrZbMp969HYjEomd5arFYqMOKrEZgSwXEvdKQ44b1I445fIo1d4tn01O2APE/7wDCgYfoprg63aaWIRo+TWdZmKtNHJMcxENDiI4uxL0RjcTtMYmLb7WF4gkQCmk1YH5v21EIVoFxRMkn2SDSCZ9w3y5si+nslGoW1hrc2cCoVCPu2pN1GF0SjsK68JTaaTdgS0dg1nfRUf8Izn8NmEyq7QXme9kGnfGq4s1NFNHqd1ay+Re1fyPudVApyzbj3jXBMk0JtisSk+0YhXiCZ1Md8aM4zE2SbSjsdRwr/uyYW845orLSNG2SR0zXRKOyYo2xveGdXvFKBsKqKaOyCSATWPGaEU221khYjnO4YH9cb4WvBlGfu49aWbms2QQUxY+iNjmjcDMGud56rViOi0eNkSkFi/nVGxRgQaInGWkxHGk0PtyHZ3KRAnHis6fZIPEE7tbgQSHtCaOylvOWXndUeicV1y4bmhvv3slyVSHGvdFLj1r3j7NwR/yIa70knUuyh9NS2aAxTkZrGLlCqJf4DSc/Mie1hTIzW9ACFrumIRgzIDW9do2OiUSn1u0qpFaXUhlLqnFLqH+157Z1KqZeVUlWl1JeUUof3vDaqlPrvrfetKqX+5S3nveN7h4HVjXGmx7wzMbiNYUB2p2X1v7Xl9nDuiJkvUCROQtptAHtFo+GZXdU25e2ARKp6JJby08TPZs799OvylqTE9UpHNG56x6m0UoFwsyyisQuiUdhsjHti06ZN28hIIo3dE43Cut8bGRtw4x5OhOruDmQfkk7r47D3anQy0vi/A/OmaU4B7wU+ppR6VCmVBP4n8BEgDpwGPrPnfR8FFoDDwJPALymlvh+gi/fue1arEdKTYqbSJpWCXLU1IXm4rnH9cokGARJpcQKEPaJRpTwzQbYp7wSZUFUYkbY23RJLBQEoZd1Pv65s++X+9Ugspo9rlaC7A9lDpWISbm5ImngXRCJg4mNjzTuZLDdFGiW1sSuiUVhT3jAUgxtTc3jMO79X+4V4HHw+kwxpEY1WYJrmWdM0d9r/bP05Bvw94Kxpmp81TXMbLRIfVko92PrenwR+2TTNkmma3wE+Dvx067V7vXd/02ySqcWYjg1vfnSvpFJQqIRo4PO0aCxe0ZNAYkYWsrBHNOKdon/QAeudRpCJ0V1Jx+mB2LTOly/lGy6PpCX6gzv3/kahQzvSWKp6p+6hsmkSNiXS2A1ejRQDjI82wCeVT90QicCah1yMO+mpYQ+X/ngUvx+SsYZEGq1EKfUbSqkq8DKwAvw58Frghfb3mKZZAS4Ar1VKxYDZva+3/v7a1t/v+N7bXPvDSqnTSqnTuf2Sb1wssso06ZT7CzOvYBi6ULtAwtNmOIVrets1Pie1HaAnR78f8o1WKo5H6lE76Tijko7TC7GZlmgsun8fK7tBwiOysdYLHdHRmPCMaUOl3JSaxi5p37/1sndEYyfSOCrrlW6JRmG96R0XYxGNg2GklYhGKzFN858Ak8AT6LTSHWACuHX1v976vok9/771Ne7x3luv/dumaT5mmuZjqXaXeI9TuZSlzCTTM7Jr16Z963KkPB1pLCzryEfisNTJgd54jsehUJ+Ceh12vBEZ6ojGMVno9EIsqdOuSyWXBwKUa6NMjLifJruf8GJj8UrZ1PVwIhrvSef+1ca9I/rbkUbZJ+0abWg04bn01IlJybrpB2PaR1ZNi2i0EtM0G6ZpPgvMAf8YKAO3zhJTwGbrNW55vf0a93jvvidzTuvh9EFJcWyzb0Tjql7Eimi8QSIBhd3Wfo5HFqqdSVJEY090auJcdt9sNqHaCBEOyf3rBU+KRnFP7Zp2jz8vNYbvRBrHJUrVLZEIrNfGPfMZ7MyHUxKo6AfDUGT9IhrtIoCuaTwLPNz+olIq3P66aZoldBrrw3ve93DrPdztvbaO3CEyF/QnePqobN21ucnWuFh0dzB3oVjQE2fC8E76kNskElDYbolor02Sko7TE52auE13jZ7aC1UR/b0RCkEoWPeU6Khs+bRoFCOce9JJTyXimbYbnUhjWKJU3RKNQrkWor5RdXsowJ75MCLrln4wDMg2UyIaB0UpZSilflwpNaGU8iulvg/4APDXwJ8AJ5VSP6yUCgH/EThjmubLrbf/DvAflFKxlsHNh4BPtl6713v3NatXdArf9AnZeW1zU6Qxn3d3MHehUNQTZ3tyF1qicavlqucx0RiekIVOL0xMgJ86pbK77pud+ycO/z0TnahTwht2/80mbO34JdLYJTdFij0i+juRRnmWdk07Yry+M6rLNlymU64RFdf3fkinYaM5wfaqd7PgBsWpSKOJTkVdAkrA/wn8c9M0/9Q0zRzww8CvtF57M/Dje977n9DmNleArwC/bprmXwB08d59zep1vXuePhFxeSTeoe3CmQsd8nQD1cJGgKh/k4A8ezskk1Aoh/Q/PLBQBanh6BelIBbYpFR1N3W+s8iRSHHPRCebnklPvaldg4jGe9L+EXlJNHYijZMSpeqWmyLGHriP5TIomoxFveOqvJ/oZMKtDm/LEkeWtC1x9/a7vP6XwG3bZLTadPzD1p+e3rvfyWQViiaptOSXtwkEtHDM1g9C7ptuD+eOFMqjJEbL3MaT6b4lkYD85ggmoDwwQYLUcAxCbKRCaSvk6hg6909Kh3smGvGOaGwLDhGN3REMQniswfqWd9JT28J/fEp2Srvlpojx+vqNYnGXKK83GGcL36SkbvRDRzTmfRwyzaFs4yUrJQ+TLQWJ+9cJeqf/sidIpSAXmPF0pLG4NU5ifMvtYXiKRAJ2dn1U8U7hfydSJTUcPRMbrVLadrfeupOeKqK/Z6JRJaJxHxOdanou0hhS2/jCY24PZd9wk6GRB1qIlddqTFCWXbg+6YjG3Ygnnqt2IDOth8lvjpAa9cYuopdIpVo1jV4VjaZJYXeCxKQ3rNC9Qju1uEDCMw/U8qZOa5yIyc5Mr8TGdyjtuisaKxs6hX9iSkR/r0TjHhSNagvGRHR0Q2SqJTY8FGkMU5EC4x64KT3VE6KxIaJxAG4yahxSMxwRjR4mVwmTDEu06lZSKcg24t4VjdUqBTNOPCqOjnvxpGhc061RRDT2TnyqTrE2BaZ79YTlot6YCUckJa5XYsmANsLxQKSqIxrHhzOlyw6iMeWZWjjQ93DcrIpo7IFXpae6THmjKaJxAEQ0Cq6S350kOSXRqlsxDMjtRLR7atODBcf5PAUSJOJuD8RbJJP66CnRWKwRoMZIVNra9Eoq3iTv8r2sFLXDtIj+3okmA6wRxdx0/7PYEY2iN7ommvB5Kj21WmkSpiw3sQduSk/1QMS4vCmicRAmJmA81BDRKLjA9jb5ZpykRKteRSoFhe1xGg3TE7tzt1JbLbBBhIQhH6+9tCONeVKeWeiU1+oySfaJYcAaMXaX3Wt90440TsTddXHdj0TjPuoEqa65vzHZEY3iYtw1kaiPNRXzhNgAqGw0dXrquGzAdUu7fNcr6amVMjIfDoiRMsmQFtEoOIuZzZEnSTIlk+itpFJgmkpHrDyYolq6oifxxLQsZPfSSU8dmfFOpHG9VcMhDcV7xpjVKaG5Rfd6UpVLOr04nHDXxXU/0kmNy9XcHQh7RaPUpnZLNArrXoo0lpuMI+mpveD3w9SU6Z301KoS0TggxrRPIo2C82xcylMnSGpGanVupZ037lUznMJVvQKKH5CF7F7irXRdL4nGiqTj9I1xSP9+Zy9VXBtDZV03xB6Py2etVzwpGsXQqGuiUVgzpzA3vCEaK+WmGOH0QSSiWPfFPCIaffoeynzYN0baR9Y3I6JRcJb8BR2tSs5Jk9VbSaX00bOicUmbFyUOyuS5l2BQp+MUAoZnRGO5bIpo7BPjiP79zl7ddm0M5Y0GY1TxR+T+9Uq7JVwp734JREc0RqU2tVuiUXR6cWnH7aEAOrVRIo29E43CWiDlDdG45Zf5cEAMA7JK0lMFh8ld1rNo8pA8gG+lLRqzGJ4UjcWM3rlPHJYH760kElBQHqpplBqOvjGO64Kc7HX3IlWVTRH9/dKJNJbcc79t0xGNMUnp75aOiYp72eE3Ud1Cahr7IBKBNX/cG6JxJyjP0wExDMg2E5gZEY2Cg+SX9O598pg0Or6Vm2yNPSgaC1m9c59IS2rxrSSTUCDunUhjxSeTZJ8Yx3QdaHbVPQdjiRT3T0c0rrtfN1+pgI8GozERHN3S6fHnvtYAoFL1SaSxDzq1qS7fyFoNduoB/TyVe9g3hgF1M8DaqnsZOHYiotGj5Ff17r1EGl9NMqlbeWWDc94UjUV9bBu/CDdIJCDf9JBo3JIajn6ZmFSE2CJbcK8OrVxRcv/6pCMay+5vblXKJmEqqIhsknZL5/5temMZV93xSU1jH7RrU90Wje1o/0RwRzv0CH2RTutjNuN+BocdeONpI7yKfFb/wol76qvx+7VwzIwe0r0aPUZhzU9A1WUdexsSCSjUI94RjdsBiVT1iVJgBEtk19yrQ6tUJVLcL530xnoYqlVXx1JZq2nBIS7GXdO5f2X360BNEyrbfh1plPTUnohEYK0x6XrrlI5oHK27Oo79TjsTLlMagYb79eJWI6LRo+RLfkbUrsyhdyCdhmxg1puRxs1REiObKNH7ryKRgMLupGdEY2UnwAQVGBtzeyj7EiO0QXbTvUXi5pafMFUYFcOwXhkZgfGRGiViUCy6OpbKel2LximJNHZLJz216r5o3NnRbbAk0tg70Sis18OYa+5GGttT8sTY8AkdJ+mUT5lJ15+rdiCi0aPkN4IkRzZEeNyBdBrdQNWDorFYDZEIubtz71USCdiojVPb2HJ7KJgmlHdHmBjZRT5o/WGEq2S33IvylaqjxIMbcv/6JDFV0/1uCwVXx1HZaIho7JFOemptXBekuUg7SiU1jb0Tj0PT9OGyZrwhGsfdq1EfBm7y3BhCB1URjR4lVxknOS7C404YBmTqCU+KxsJOmMSEN2zQvUYyqY/F8ohWbS6yswMN08/EqPt96vYrqcgO2d2oa9cvbYWIBd3rE7nfMeJ1vbhxO9K42RTR2COd9FSirrtRt7ObJdLYO7Oz+riyMQFNN03F9FFu32C01zgiGgXnME3yO5MkJ0V43Il0GrI7U1o0uiw+bmJri0IzRnxK6gJuR9scKN+MadXmIp2d1ZDcq34x4g2yzSRm3fmUJtOE4k6YuET1+8YwWv1u3Y40VkwRjT0SCsFIoME6EddF441I45YemNA1bdG4zIyrZRud+VDKwwciEIBEtC6iUXCQSoV8M04yKrnld8IwoFwLUd1WN2YsL1AoUCBBIu4hIesh2qKxQML1usbOzuqYpOP0i2GYbDNGecn5ZnHlsrY2j4+5n+q8XzGm/d6INLZdcKWIv2uUgmi45q1I42hdUsV75IZonHXVQbUjGifl/g1KOt2KNGYybg/FckQ0epFsljxJkkkRHneibWvsubrGfJ4icRJJefDejptEo8sLHanhGBxjRrdryL5ScvzapdYlY+OSkdEvxsERshiYeZcjjVtKIo19EJloaNHoEefN8TFZs/TKzIw+ekY0RqTdxqAYM36yKg3Ly24PxXJENHqQ+nKWEjFS0+73z/IqnV44GJ4SjdXrJbYZIyH37rZ4KdLYsRiXdJy+MQ5q19LsRefvZTs4Fo/JQrVfjNmgjhRn3M3WqGz7RTT2QXSqqdNTXRaNnUijZG30TDgMkXDNddHYmQ9FNA6MYSgy/gNw/brbQ7EcEY0epHR5HRMfydkRt4fiWTq9cEh7qldj4bKOniVmpAXA7WgXiXtBNEoNx+AY87rdRvbqtuPX7ojGpExj/ZJK6WP2usvumzsBSU/tg2hUeSvSKC0a+2I21RKNLt7HznwYc7+Fy37HMCBrpmBpye2hWI7Mth4kd0l/epOH5Al8J7yanlpY0vVV8YNiQXY7xschNNLwlmicksdgvxjHdWQou7Tr+LVLRR1hjKVlc61fOvbwLvo1mCZUdoOEA7sQlAVrL0QTPi0aXYxQwZ5Io0x7fTGTNl2PNJY3mgTZZSQiPYsHxTBgrTHJ7jWpaRQcIH9NC4/kEdl1vRM39cLxkGgsruj6qsRhCV/diUS0QZ6kd0SjpOP0TepEDIDsqvNpacXl1gbNAVnk9EvnOZp3bymwvQ0mPm2iIvREJBHU6alrzhtR7aUdaQxPSC1/P8weUO6LxlKNCcqSemMB7edqbmnHW+7+FiCi0YPkV/SufXJOrKvvRCgEU1MmGd+sp0RjIasdbxNpqWm8E4m46Q0jnE39MJd0nP4ZjY4RYc0V0VG8psMb8UOyyOmXzuJmzb3PQEdwSD1cz0STAU9FGscnZQOuH2YPB1hmFnPNRdG4Xtcp4iIaB6azGbczdcOxbUgQ0ehB8lm9mG3Xfwm3J51WZEfnvCUa8/retQ1fhFeTSChvpKeua4EfjopoHAQjUCTrgugoZXYYYYfx2ajj1x4WOjWNm+5tUHZE4/hw7cg7QTSm2GKc3YJH+jSKaOyL2UNBaoxQWHWvtri83pBIo0XcZNQ4ZHWNIho9SL6oUzxENN6ddBoyfo9FGkv6IxWPuzwQD5NM+7whGos6oh+Oi2nRIBihDbIbzqeIFrN1YpRQKXlQ9ksoBFMj22SrE66lUXVEo9TD9Uwkoo/reZeNjCoQZJfgpGRH9cPsAb3mW1l1L723vGGKaLSIm4waRTQKdpNfCzLhrxKS5+9dMQzImB6radwMEvZvMSo65I4kUn5PiMa1fJ1JNvBPyWp1EIxwheyW8wuNYsEkTlF21wbEmNwi23SvxrgjGidlOdIr0VaQfS3vbj1otQphVRXl3yezs/q4nHWvrKVSEdFoFW3RuMr00LXdkKe0B8lVxkiOuds3az+QTkO2FveUaCyUR0mE5N7djURSp6c2N939OZUKDWKUZJIcEGNqm+yO8ymipTUlotECjOiuTqNq9zBxGBGN/dMRje764FCpwLhZkZ4bfdIRjQX3dpvLZSWi0SKmpiAaNbnKYYk0CjZjmuS3J0hO7Lg9Es9jGFDYnaSWc3nG3ENhO0xi3PmedfuJRAKa+FkvuLs7XioiotECjHidfDNGo+HsdYsbQWJqXXr7DUgq0dSisVBw5fod0RgR87Beaaenui0aq5WmNlGRSGNfzMzo4/K6ez+/clVEo5XMzysuj54Q0SjYzNoaeTNBMupujcJ+oF1snNschR0PiOzdXQqNCIkp53vW7SfaJkGForv27MWSEtFoAUZKbwIUl53dLClWRomHqqDE5n8QDANvRBrFkKpn2s/S/Ka79RCVjQbjSHpqv4RCEA9usFx2bwOsvOUX0Wgh8/NwSR0T0SjYTDZLniRJcd+8Jzc5VOXz7g4GoFCgSJx4VKzj70Y7m7Cw5q7TXmnDJ6LRAowZfR+z55wNd5R2xoiHJao/KMZsgDxJmjmXIo1reoM0HBtx5fr7melpfVwtu/sMq25KpHFQZsPrLFfdc4IubwdENFrI/Dxcrs1iLklNo2AnLdGYSsvu+b24yaHKC3WN+TwFEiQScu/uRifSuOFuZKG0GRDRaAHGnF7sZy86Z6RSq8FmfZzYpMM5sUOIcXCUBgFKS+7UGFeKOksknBDnt16JxWDEX2d1JwZN9zYrK2VTRxqlprFvZifLLO+4U59tmlDeCUqfRgs5cgSqjRD5a1tuD8VSRDR6jO3rBcpMkpyVXdd70Y40ekU0NnM60pgwpFfV3fBKSlWpHBTRaAHGvF4o5q5WHbtmu1+yRPUHp33/stfcSfGvlEQ09otSMD1VZYVp2NhwbRzVqimRxgGZjVZZbhiutL7Z3oam6WPCtwUjsva0gvl5fby8GXfdKd5KRDR6jPwl3aQ3eVB27O7FTempHhCN61fXaeInMSMP3bvRiTRW3Fsk7uzAVk1EoxUYx6cAyF5zrpa3Ixolqj8wxqw2oMmuaAWGMgAAIABJREFUuiPAKyWdnjqWkDmvH2Zi29raf33dtTFUKkhN44DMJndYYYZm2bnNtzbtuuKJUfHSsIq2aLzEkaFquyGi0WPkW7v1yXl5+N6LyUkYHTU9E2ksXNP3Ln7A+Ubn+4lIBHyqSWHbvUViR3RQlJSqAYkfi+Gj4ajoKGa1827MEPOUQWmn+Wczzkc4ACrrdcap4ItOuXL9/c50os4KM65aqFa3lEQaB2TWaNAgQO7ipuPXbgfCJsbcdTQfJjqRRuaHygxHRKPHyK/onZ7ktCyG7oVSrV6NHhGNbffIxGGJXN0Nnw/ioSqFHfd+Tm3RGAvXwC/pxIPgS8ZJkSObdy7qV7yqVznxGXdTnIeBVEofs0V3PgeVjYYWHFMiGvthZrrpfqRx2y81jQPS6dV43vlI4w3RKOn+VjE1BfFoQ0SjYC/5jDZ2kH7V3ZFOKzLBOU+4pxZWdHpeQgT/PUmOVynUplyp34A9ojHmyuWHC78fw18gW3Tu975t2iJR/cFJJEDRJLvmTlp9pdwU0TgAM7M+8qTYzbknGqvbPok0DsjMnN60Wb7ifIpoRzSGRTRayfy80qJR0lMFu2hrn/bur3B3DAMy/hlPRBoLGZ3akZB2KfckMbFDwYzrCnwX6IjGpEQZrcAYXSe74VyNavG6dqSLHXKvr9mwEAhAYrRMbtMdAV4powXHpNzLfpg+qGtSM1fdMTKq1aDW8EtN44DMHtabbstXnU8RvSEaHb/0UDN/1Mcl/3GJNAr2kV8LoGhKBKRL0mnINpPeEI15HTWLx10eyD4gMVUjT9I1V7GOaJSaOEswxitkq86tOIoZvRsfPRxx7JrDjDFeJrvljmirVpFI4wDMzOvNmtXr7rSfqbayKSXSOBjTR3Vq7/Ky89duT8PhSZEEVjI/D5ebhzCviWgUbCJXHiM2WiUQcHsk+wPDgGwtRjPrfnpqcc2HoknUvf68+4ZEtEmBhGt1OMWiPsZmxObfCoypbbI7zgm4Ur5OhDUC05LHbwXG1DbZ3Ygrvf4qYqIyEG2xsbLizvXbzpthKlLTOAAjiUlSZFnOOL8s70Qap0QSWMmRI7Bthshedr5O1S7kN8RLNBrkt8Mkw+6k7O1H0mmomwFKWfetorObYyRCFfFV6YKE4deiMZt15fqlgl4cR+fEtMgKjHid9eYUOw5lyBUL6HYpUvxtCUa0plsXudDrr7LtZzywq53NhJ6ZaaWnrubcWc61I43jahtGxZiqbyIRZllmOed8bXFHNEZk8WIlHQfV68OT0SSi0UsUCuRJkoy4L4D2C51ejaUgNNxJzwFgd5fMToT01JZ7Y9hHJA+MsM0Y1avuRIhLq9tMskEgLQWoVpBK6tTsXNYZY6Piup+4bw1CEim2AiPZ1KKxUHD82pWdIOGgzHn90m6ZspJ3ycioHWkcrYvwH4TJSS0aS87XFnf6NEYlxc1KOr0aSxEc21G1GRGNXiKbJU+SVEIcrLqlPWFmXFrwdMhmyZAmHZPFTzck5nQaU/6S8z2pAEqruzpSJY5TlmBM66kke9GZGtVSOUh8pOLIte4HjLSiRJzdTMnxa1dqQcLSVLxvRkYg6S+yuu6SkVHrYzgeknXLQPh8zAbzrGw6n6Zd3tT3bjwmkWIrualXoxvFqjYgotFL5HI60mjIbl23tCONGbd7NWYyZEgznXanhcR+Y/YBbbqxfNEl99R8XYvG9q6DMBDGnI5yZC84swlQ3AoRG5OovlWkZnX6lBubOJXaCOFRF7NEhoCZ0aIrYgP2GOGMi2gclNmxIpnqJHWHDVTLa3XGqeCfkrpiK5mYgGRkd6jaboho9BBmJkuOFMmZ4cl/tptOeiqGu70aV1d1pHFWagK64eARnQZz7apLfRqLpkQaLcSY15Fjpwr+izth4hO7jlzrfsA4qCMMuavOC/FKI0RYmooPxPTYBqtVd9xnO5HGcdnsHpTZiQ2aps/xUv/NUp0JylrlCJYyP9fQonFI2m6IaPQQm1dL1BghOScNq7slHgefz3Q90li9mqfMJOnDkt7RDXNz+ri06k4NRWndJ6LRQoyjerGRXbJfyJkmlOqTxCMSnbIK44iOMDhx//ZSq0HNDBIelwyNQZiZLLOy406vp7U1fYxMyOdxUGantAJ3OpOxkG2SoCCi0Qbmjwe4xBERjYL15K/qXfrkIbGt7ha/H1KJlomDi6Ixc1E/7NNH5aHbDdEojPu2WCq4s0FSKgeJUxT3TYuYOBQnxBbZVfsXjuUy1AkSl162lmEc0+ni2VVnI37tjjtTExJpHITpyBar9SSmC9q70/N20vmm9MPGbFyXazgtGnM5SJIX0WgDRxYCXOEwzWuSnipYTH5Z7/ImDbktvZCe9rkeaVy9op2x0gfdcbDbbygFc+ESS+vuNBQvbYWIhbaQhqjWoFJJDLJks/anqBWX9cIqlpRUcKswZvXnwOm0uPYjOxUTwTEIM4lddhntCDgnKZVA0STiXJvWoWU2pQ2hnBaN+aIiRU5Eow3MH1HsECJzwRmTOLsRdeIh8qt64pSMud4w0oqMf9bdSOOyjrC0ayyFezMX2WRpy/mWFzs7sFUfITYhC1XLmJzEUDmyJftFeOmyDk/F01L7bRWRCATZJVt0dhMll9ERxnbLFqE/plN6/lm57Lytf6kEEd8m/gkpqxkUwwAfDedF41pAIo020XFQvezmKKzDEdGolBpVSn1CKXVFKbWplPqWUurdrdc+qJQq7/lTVUqZSqlHW69/VClVu+V7ju459yNKqeda73tOKfWIE/8nO2j7uEjGXG+k05BV0+6KxlZjZRGN3TOX3OFaY8bx/kWddKqIpMRZhlIYI+tk1+3vm1i8oh0+47PSo9EqlAIjWCK77mxNdtt4RzZKB2NmRh9XLzjfhqZUgphag7A4bw5KIDZJmoyjotE0Ib8eFNFoE51ejSvDMV85FWkMANeAtwMR4CPAHyql5k3T/D3TNCfaf4B/AlwEvrnn/Z/Z+z2maV4EUEqNAH8K/C4QAz4F/Gnr6/uOXGuXXkRjbxgGZJpJd0VjMdgZi9AdB2cbLDNLY8XZnLhiUR9jcXH7sxJjvEy2av/Csbika79jB2WRaiVGaJNsxdl6+vwVLXJSh6WOfxBmDuq1g1uRxhglGJd7ODCRCDOssLzknKnQ+jo0mj4RjTbRiTSWItDY/2ZRjohG0zQrpml+1DTNy6ZpNk3T/DxwCXj0Nt/+U8DvmGZXJd3fixak/5dpmjumaf4XQAHvsGrsTpLfHCXgazDljnP2viWdhmpzjPKqeznjmc0x4qMVgpIx1zVzh3w0CJB52dlCnE6kMSX1jFZiTG2R3Z6y3YyjtKJrGuOH5UFpJalwldyWszXGuWv6XiaPSUHcIEwf0vvkq9ecb0NTKkGsWZBIoxVEIsyyzPKSc1kwnQw3EY22MD4OxmSVy+YhyGTcHs7AuFLTqJRKAyeAs7d8/TDwNuB3bnnLDyqlikqps0qpf7zn668FztwiMM+0vn7rNT+slDqtlDqdc7MJ/J3Y3SW/M0FyvIqSAEhPdHo15lz6we3skNmJkp5ypkfdsDB3TKfCLX3H2Ybipbze7YtNS3sUKzGiNXbMUTZtvp3FjDaLiB+N2nuh+wwjsk225uzPNLdcY5INRuckP3UQJmcmGKfCynXna0OLBZOYWRTRaAVt0bji3FpGRKP9zM/sDE2vRsdFo1IqCPwe8CnTNF++5eWfBJ4xTfPSnq/9IfAQkAI+BPxHpdQHWq9NAOu3nGMdeNV2qWmav22a5mOmaT6W8mIBRS5HniTJKWlY3SvtlNBMMYgrnuPZLBnSpGM156+9j5l7SH9Mly44XNO4pFPiYrNi3GAlRkrvjtvtwFksmIyww9is9NywEiNWJ9tMOppClcs2tWuj5PUPhIpGmGaVlYzzG6elkqnTU0U0Ds7UFLMskysG2HVoKdhxMFYFCA1H3Z3XmD+M7tV4ff+33XBUNCqlfMD/AHaBX7jNt/wkui6xg2ma3zZNc9k0zYZpmn8D/N/Aj7ReLgO35ihNAc6GLqygJRpT8f2f8+w07UhjppG40WnYSTIZLRoNcQDshbmTOqpx7YqzhjSl6+2aONlVtRIjraeT7LK9rrSlNYirEioo6cVWYqRMKkxQue7cMzRX8GvR6MWN3P1ENMoMK6zmna2PME0orSnd81ZqGgenFWkEWF115pKdSGN4C0lzs4cjD4zoXo1XJdLYNUopBXwCSAM/bJpm7ZbX3wLMAn90j1OZ6LpF0Omtr2+du83ruSXtdV+QzepIY0o+tL3SSU/FcGcnpy0aZ6VvXC8kDoUJscXSirM/t9KKdmyMHpFIlZUYc7quKnvR3tri4kaAeHD/7Qt6HWNazz2587cm79hHfiNIKrgGI/vSu847RFqRxpKzKfdbW7C7qyTSaBV7RKNTDqod0RiRTCm7mH9ojBojrLyy4fZQBsbJSONvotNMf9A0za3bvP5TwB+bpnnTakAp9T6lVExp3gT8M7RjKsCXgQbwz1ptPdrRy7+25X9gJ+94B7nYAyQXZCHbK+1N6gxpuHLF8etvX8uxQYT0YamR6wWlYC6QYSnv7M+tlNV1VIFpsSm2EuOwTvfNXra3trdYHiU2erspRBgE40BL9F9yrm1DrjJOasz5NhFDRzjMjFpldcPZaF/HVExEozW4JBpHfbuED0iNuF3MH9VS6/L5/d8b2qk+jYeBnwUeAVb39Fv8YOv1EPBj3JKa2uLHgfPolNPfAX7NNM1PAZimuQu8H53Wugb8Q+D9ra/vKxoqQHHNRzItKVe9MjoK0UjTNdGYuaAjK+mjku7YK3PjBZbWnXVsLBWaepEjKXGWkjqif/+z1+ytUS1th4iHt229xv2IcUjXM2WvOvOzNU3IbU+SnHK+TcTQoRQzoTXWtsfYcnA/5SbRKOmpg+OSaEz6iqgDs85c8D6k06vx2v5f3zvyPzBN8wo3Ukpv9/o2cNttDtM0P3C7r+95/VvcvnXHvqJU0pOo9Gjsj/S0Irs5DVdOOX7tzFW96EnPSb+NXpmb2uTZzIKj1yyVWjU4ydc5et1hZ2QmQYI8S9fsre0t1iZ5eLJo6zXuR9qiP7fsTJra5ibsmiOkovt/990LTIc3YUu7+rcXqXbT6XkrkUZrmJoiRQ6/arK87EwiYD4PSTMHsyIa7eLwYX28nN3/5nuutNwQXk0nr1xEY18YhiIzcsidSGPL+KNdWyl0z1xyi+u1FE0HvXBKm35igTIE9v+un6dIpTjOec5fs7E+zTQpNiLEImI6ZTWpY9pTLrvqzIex49poSB2/FcxM6TTflRXnrinpqRYTCOALjzMTXnfsPuYyTVKNVZiZceaC9yFjYzAd3uDyWswdh38LEdHoEdqiUTLm+iOdhqzPpfTUrK8zBqE3Dk7XqTFCdsU51+BiZZRYSGriLCeRYIFFFlfsSzeuFTcpM0k8btsl7lvCB6KEKZPNOyPicit6sy01LQZiVjAd11U5bojGOEVpm2IVkQizYyXHWvrlMw3do1EijbYyn6xwuXnwRnh+nyKi0SMkk/DzPw/Hjrk9kv2JYUCmnnBHNBaDnTEIvTF3SC9Ql84659hY2h4jFt53Zc/eZ3SUhbElrq1P2lZXVbqgJ9y4IVFiy/H5MHx5skVn0uzzF7WTYGpODMSsYCap04qdatUAt0QaZQK0hqkpjoyucOnSvb/VCvIFRDQ6wPxcTfdqdPIDagMiGj3Cgw/Cf/2vcPSo2yPZn6TTUNqdYHclDzvOGitkNsaIjFSlL24fzB3RqYxL33GuhUKpNkFsSvqh2sHCgsLEx4UL9py/eElvLsSmRWjYgTGyRnbDmZ9t7pI2EEsdFgMVK0gZCh8NxyONiiZTiREISk2/JUQiHA1c5coVqNtc7luvQ2kzKKLRAY685QBXA0dpPPhat4cyECIahaGgnY6/zCxcu+bchXd2yOxGSU9KumM/zD2ozTeWzjvj2Li9DdtmiFh0f9cVeJWFN+mWQYtn7Pk8lK5poRE/sP8NBbyIEdokW3GmNi23pD/zyWMRR6437PhjUxgq53ikMRqs4JuWKKNlRCIc5SL1uv1LmXamZJK81DTazPwxP/W6cswV1y5ENApDwfHj+nie486mqGazZEiTjku6Yz8kT8QZYYdrl52J/JXy+jqxpNRR2cHC9+lUicWv2DMzFq9rMRo/JO1t7MCYqJLdnnLkWrnlOqNsMzEv7m+WEI0yYy6zsuzchlipBDHfBkxPO3bNoScS4VjjHAAXL9p7qY4Bo38NEgl7L3af8+ij8OEP6/7U+xkRjcJQcOKEPp7jhLOicXVVi8aURK76wTdtcIDrLC078yQtXW6lNxqSSmUHkSffiEGGxW/Zk25czOjNmdi8RKfswIjukKtFHTH4y2VNUuRQaYlSWUIkwjSrrC47aCpWhJhZFNFoJZEIR7e/DewRjaYJn/0sFAqWXqrjYJxo7n8143EefRR+67dgbs7tkQyGiEZhKJidhfFxk0WnRWMmo0XjrESu+iIW46BaYinnTB1VRzTOSAGqLSQSLISWWLxoj1FNKacXxBJptIdUrEGNEdYd8KXKl3ykyENENgAsIRplhhWHaxpNYvWsiEYriUSY2/wOwSA3asOfew5+7MfgU5+y9FKdSOO0GIsJ3SGiURgKlNImHOdGX+eoaNxZylEiTvqQGHP0hVLMhQosrTkjAto1cbGD0lPMLhYOVFgsJWzpR1Us6HNGY7IrbgdtA8zs9Zrt18qtj5IaXZcIh1W0Io2ZvN+xvrelQpN4My+i0UoiEfzbFeYPmzcijZ/+tD5aXLDaEY0HZP0idIeIRmFoOHECFtWCo6Ixe0Gn4aWPigjpl7nJdZYqMUdS4krLVQBih5yp27ofWXjNCMvNGcrfsd7FobjmI+LbwC+BfVswpvWSIHPefjfjXGWc5LgYiFlGK9LYaKiOGLCbUtHU7TZENFrHlJ6bjh6q6Uhjswmf+Yx+LZOx9FLt35PEvH29dYXhQkSjMDQsLMDFnQPULl937JqZq7q9R3pOauT6ZS6xxW4z2KmvsJPSaqsm7kjU/ovdpyy8RYerzn/uO5afu1QOEB8pW35eQTN3RD/Hrr5iv5jL7UySmnK2PdJQE4kwg85NdSJF1TShtO4T0Wg1rXTtY7NbOtL47LOwtKRfy2YtvVR+pcYkG4welLpioTtENApDw4kT0DD9XLoWgIYzZgCZlumAzJn9M5fWqXDtedFOSjnd+Cp6NG7/xe5TFt5xEIDFp61fuRarIeJjEp2yi6MPBFE0WXzZ3ufn9jaUm2FSMZsb0d1PRKNMo9MXnWi7Ua1CrS6i0XJaovFoqszaGpQ+9acwNgZvf7v1kcalbenRKPSEiEZhaGg7qC42jjgzawKZrK7HSacdudxQclBrDJau2Z+fWizClNogMCaRYbs4/pD+2S6+aH3vzeJOmHhY2tvYxejxgxziKue/Y29NYz6nP+uplK2Xub9opaeCM5HGdo8/EY0W0440xksAXPjjF+C974WjRy0XjbmVOily0qNR6BoRjcLQsLCgj0623cgU9QJZRGP/tFPils5bLzJupbThI+a3v17rfmZiAmbC6yxeH4cdC9MPGw1K9UliU861FLjvOHGCBf8lFi/aWzSau6Jri1Mz4tpoGVNTjkYaS1rT6D6NccncsIx2pHFS12tcXI/DBz6gFxnZrKUGY/m8KZFGoSdENApDQyIBsamGs6JxY4zJ4BZjY45cbigxjk0SoMbSYtX2a5U2g8RGK7Zf537nxOFdFptH4YUXrDtpsUiROPGY9ES1DZ+PhfQGi4WYrZfJndc9PZJz0vrGMoJBxsM+pka2HIk0tkVjPG6CT5aSltESjUdC+iZeCJ2E7/9+bW1cr9/4wVtAvhQQ0Sj0hHzShaFBKTjxACzikIPq9jaZ3SjpKamxGgTftMEBrnPtkv31TaWtELFxMd+wm4WHx/Tn8Otft+ycZi6vRWNSpi07Of6An1IjQnHFvs9J7pI2M0rNi+u0pUQiTI+tOxtpTEmqv6W0ROPkxnUMleXioe+F0dEb6UwWmuHky6Mk/SWI2btJJAwPMvsKQ8WJB/2c8z3ojGjMZsmQJh2TGquBSKeZY4ml6/b3ayvtjhObsL8H3f3OwiMTZEmz/rR1kcbytRINAsQMWaTaycKbdarh4l9cuMd39k9uSQvS1DFpfWMp0SgzwYKjkcbYtPT4s5RWyw0+/WmOmhe4OH5S/7stGi2qa9zagkptlOTkrvRKFbpGRKMwVCwswLXmHNWLDmy1ZjJaNKYkXW4g0mkOco2l7Ii912k0KDWmiEUc6nx9H9OuL178W+saxhUvbwAQn5FFqp0c/zvzAJz/in2ti/IrNfzUiS0kbbvGfUkkwow/66xonJNosaWMjuo/3/wmx0LXuVBqRQGNVlsMiyKNhYI+JhMyHwrdI6JRGCraDqoXzjsg5FZXtWiclU7jA5FMMsd1lkphK2v8X02xSIkYsbg89uymIxqvj2FVA87ikq55jR+URaqdHH3LDD4aLD5vX+1vLgcJCvjSYp9qKa22G46IxkITHw0mD0rPW8tpm+G8Lsy1a4rdXSyPNLYfyylD5kOhe+S3RRgq2qLx3PWwpS5jt6N2PUuBJOlDNkfIhp1AgLlwie16sGPjbgfbS3m2GSOWEsdGuzl2TB+trGssXdbmKbHDk5acT7g9oyHFobE8i5fs+5zkin5SviKMyLPTUiIRDjYuU6lg67MUoLiyTZQ1fDNiHW457bYb7zpOswlXr6Kd/nw+y0RjvpUEkjwgmRtC94hoFIaK48f18dzOIdtnzdxF3bohfUQiH4MyF9dRjWvX7LtG6aLOp4qlZaFqN2NjcHCuyaI6AV/7miXnLD5/FYC41FDZzvGZCuc3UrBpT3ua3MYIydENW859XxONsrB7FoDFRXsvVVrdkR6NdhGLweHDHH2XXtBcuAD4/ZBMWpaeml/SLa6SB8X6XegeEY3CUDE5CTOxLUccVDNXtZlDek6MOQZlLqXNhJaW7LtG6apepMYOjNt3EaHDwgkfi2MPWyMaazWK5/TWuLSEs5+FhwL6Gfrcc7acP1cJkwrb32LnviMS4fjWi4ADojHXIE5RRKMd/Of/DJ/6FEePaYOaixdbX0+nrYs0XtIbQsljEUvOJ9wfiGgUho4TR+uO9GrMLOsWEWnJzhmYgwf10VbR2KqJix2csO8iQocTJ2CxcQS+8Q1oNAY72QsvkNvVroIiGu3n+JvjlIhT+PKLtpw/vztJakpa31hONMrR2sv4fKb9orFkSqTRLp58Et7+dmZmIBRqRRpBm+FYFWm8WkXRJHY8Ycn5hPsDEY3C0LHwUNAZ0ZjRu4AiGgcnfWgUP3VbRWNxWafjxOfF5t8JFhaguDNBYTMIL7882MmeeYazvJZDB+qMSTaV7Sw8ojdWzj9jvaNKowHFRoRUbMCNBOHVRCKMssuhAw37ReO6X0Sjzfh8cOSITZHGlV3iFPEfnLXkfML9gYhGYeg48bpRchisvWLNw/VOZIo6LVVE4+D4p1PMsszSlbpt1yhldX9GMcJxho6DqhVpjs8+y4vBR3n9G+TeOUHn3r1gfQppIVPHxEfKkN5wlhPVTqYLB3fsF42VILFAGSYkc8NOjh3bIxoNwzrRmG2SIgczM5acT7g/ENEoDB0nHtCLkcWX7d3JzmyMMR7YkTnTCtJp5lji2sWabZcoFXU/qljMtksIe+gIj5GT8K1v9X8i02TnmW/wcv0Yr3+9NWMT7s6RI+BTTc4Xopa1TGmTW1wDIDktGwCW03LdXJgps7hon4G4aUJxe5zYhH3Pa0Fz9KhOTzVN9A51paL/DEiu4Cepip2NBkHoBhGNwtDRXqyeu2yjS+b2NpndKOlJMXOwhHSaeS5z4ZJ9j6RSSW8myBzpDEeP6vSqxdT3DCYaz5/n5Vycuhngda+zbnzCnRkdhUPpXR0lPnXK0nPnzuvWKamDIUvPK3Aj0pgssb5+o4G71ZTL0DD9xCLSGN5ujh7VP+98nhtpTRbUNeY3R0iOVUBJxF/oHhGNwtBx7BgomixmbKxdy2TIkCYd27XvGvcThsHrOcOVlVHW1uy5RGnTz1Sggt9vz/mFmxkZgcOHYXHsdVo0NvtcYD7zDC+i1aJEGp3jeNtB9RvfsPS8uctlAFLSqsh62pHGqI4O25WiWtLdi4gnRHDYTbvn7YUL6PRUsEY0VsdJTm4PfB7h/kJEozB0jI7CfGyDc1tzlqRx3Jbr17VoTNmU/3O/kU7zCM8D8MIL9lyiVBklFpJJ0kkWFmCxNg8bG3DpUn8nefZZzoTezMiIyYkTlg5PuAsLDwY473/A8khjfkm7pqbE6t962pHG8DJgv2iMGdJuym6OHtXHixe5EWkcsK7RNCG/O0VSzKiEHhHRKAwlC3Nb9jqoPv20Fo0L4sRpCYZhr2hsNCjtjBELS2TYSRYWYDEfw4T+U1SffZYzU2/hNa9RBKQMzjEWFqDUiFD4+nlLi+NyK9rsKvmAWP1bTivSOB9Y0qnhdonGjH6OxmYkxdhujhzRx4sXuRFpHFA0bm5CjRGSKYkUC70holEYSk6c0K6N5mV7RGP9L/6SHCnSR6RRvCWMjTE9WcUY2+T55204f7FIiRixKfvcWYVXc+IEbFQC5HzT/YnG1VVYXOTM9glJTXWY48f1cbEQs3TzLZeDKCWCKSkutpxwGPx+RspF5udtFI2XdV1qbE5SjO1mbAxmZ61NT81f0RlYqRmJFAu9IaJRGEpOPDzGBhGyL1nTCPcmKhXyX30FE5+027CSdJpHIhftEY3ZrBaN4pzqKO100rOH/25/ovGrXyVPgpWNCRGNDtM2FDvPcUtTVHOlAEn/mhhw2IFSOtq4vq6j/G3R+PLLlgr/0tVNAGLzkmLsBJ22G6GQvr8DRhpzr2iHpKSYUQk9IqJRGEpOPKbTRs/gp8iOAAAgAElEQVSdsaGG7emnydTjgPRotJR0mkdqpzl7psHuR34ZfuEX4Cd+Ak6fHvzc3/62Fo0z0hneSb77uyEQgC+M/1B/ovHZZ3lx5DFATHCc5sgR8PlMFn0PWisaN0ZJhTYsO59wC9EorK11RKP5yjl405vg53/esksUr28BEDsqu3BO0G67Aeho46CRxpaDcfKIlNcIvSGiURhKFh7Qv9q2pOc89RQXgw8CcOiQDee/Xzl+nEcKf8luw8/LH/ss/P7vwx/8AXziE4Of+9QpisRlkeMwkQi87W3w+cLjOtV0dbW3EzzzDGcOvQdA2m04zOgoHDqkOB/7LksdVPPVcVLj0qrINqLRTqRxcxNy7/+Q/su5c5ZdopTZxU+dyWOGZecU7szRo3D9Omxvo3eqB4w0ttNTkwsyHwq9IaJRGEoOH4agqul5smrxAuWppzh7+N0AvOY11p76vua//Tce+bNfBeCFTz4PxaLeIX/55YFPvfW1F9ghRCwp/Tac5j3vgbOrSS5zuLdo4+YmfOtbvDjxOKmURPXdYGEBFv0PwnPPQd2aeuDc7hSpiBhS2UYkoiONx7V50eLLDR3yv3wZGta4ZZbydWKUUGkRjU7Qbrtx+TI60jioaLyuHYyTD6UGG5hw3yGiURhK/H44PrfNubUUfOhD1rn/LS3Bt7/N2Yk3c/gwTExYc1oBCIVYeNcRQiF4/kzr0fTgg4OLxmaT0jd1uwepaXSe9+hAIX/GD/QmGr/+dWg2OVNd4PWvlxI4Nzh+HBbLM5jlMpw5M/D5zKZJvhEjFRerf9toRxpP/wEAi+//1/DTPw21mg5XWUCpBDHfhm7GKthOu+3GhQvo3bNB01MzdYLsMnlA0lOF3hDRKAwtJ944ycupt+k0x1//dWtO+pd/CcDZyjyvfa01pxRuEAjoNMSOGc6DD+qUxrW1/k/6yiuUKtolLh4ffIxCbyws6D+fH/ux3kTjs8/SUAFeujYlqakusbAAa9URisTh2WcHPt/69bJY/dtNJAIXLzL/sX9EQNVZfOi9tzT7G5zSRoDYqE09kIVX0XYyfuUVtGgsFPQmQJ/kC4qUv4jyyedQ6A0RjcLQcvIkLJYS7PzIB+Hf/lv48z8f/KRPPUXdmOWVKyERjTbxyCNaNJom8NBD+ouDRBtPneIy8wAcODDw8IQ+eM974K93vofyc690/6ZnnuHig3+XrS0lJjgu0Wm7Mf02S0Rj7pzuCp+alYabthGNQqVCYNZgfl6xeF7d0uxvcErVEWJjO5acS7g3qZS+hV/9KjfabuTzfZ8vtzZCMlS2ZnDCfYWIRmFoOXkS6nXFK//qt+Hhh+Ef/IPWVl2fNJvwxS9y/vH/jd1dJaLRJh55RJczLi2hI40wmGg8fZqzwTcAyD1zife8B3abQf7q0hFYX7/3G2o1+NrXODP/XkCcU92i3XZj8ej3wTPPDJzmn7+g733qoLgY28bBg9rF6I/+iIUH/doM7tAh8Png0iVLLlHaGSc2KT1vneSJJ/S+jWm0irsHqGvMV8ZIhm1wlheGHhGNwtBy8qQ+vnRhHP7X/4JgEN73vu4WrbfjhRcgn9c95xABYhePPKKPL7yA3l4NBgeONL4Ue4LZWalpdIu3vhWmxmt8nvfQVSPOL3wBqlXOTHw3Pp8YTrmFbruBdlBdXR04UpW7ok3JUkekGNw2/uk/1Y4pjz12o+1GIKiFoxWRRtOkWJskFrXIJ0Doire+VZcyLu60LNsHqGvM70ySjPSf3ircv4hoFIaWEyd0jdxLL6HtVP/4j3Wk8Td/s78TPvUUAGdH3wjcyJwUrKVdv/b88+gbuLDQv2is1eD55znLa0Tku8jICHzfO+v8GT9A87l71DWaJvzKr8Dhw7y4+yALCzAmgSlX0G03YNFs2Tc+88xA58td09GN1HFpCm8bwSBMTwP60VmptIJSR49aIhrNzTJrRIklZPnoJE88oY/PXD6o/9JvpHFzk7wZJ5m0ZlzC/YV86oWhZWQEHnigJRpBN4wzjP4nzqeegte/nrNXJzlyBMJhy4Yq7GFyUtdS3WSG069ofOklGtu7fLs004k8C+7wnh8ZY4VZvvXXpbt/45e+BF/7Gvybf8OZl3ySmuoyCwtwPhfRLlID1jXmVrVrauoBcaRygk568SKWicbNC1kaBIingwOfS+ieBx7QtY3PfruVLtOnaGxcW6ZInOS0tJ8SekdEozDUvO51e0Qj6HqPa9d6P1G1qhdM73oXZ89KaqrdtM1wAC0aL1zozy3u1CkucYTtWkDumcu8+92gaPL5U/douPixj8HMDOUf/RkuXECcU13m+HE4d05hfs9bBo805mCMKuOxUYtGJ9yNm0TjkSM6pbE8mAFK6XwBgNishP+dRCmdovrM14I6BaDP9NTSX30TEx+pOfkMCr0jolEYak6e1LX/nXlybq7lsNIjTz8Nu7vUnnwX586JaLSbRx7ROnFzEy0a6/VWk6oeOXWKsxOPA0ik0WVSKXj8wBKfz34XbN/BhOFv/kZHGv/Vv+LshRAgJjhu89hjugz82yfeD+fODVZLteYnFbhHpFmwjEOHdLZqJ9IIrQ7x/VO6rNsfxQ5Kqo3TvPWtcOGCYiX5uv4ijb/1W+R+8WMAJB87YvHohPsBEY3CUNMWCt/+dusL/YrGp56C0VEWp5+gVhPRaDdtM5wzZ7jhoPqd7/R+otOneWn67wBipuIFfuBtG5zmu1j58h1cjH/lVyCRgJ/92U4veRGN7vLkk/r4JVp/GSBFNVcKkhKrf8cIBHSA8SbROGCKaumqvn+x+eiAoxN6pVPXOPp3etu8aTZ127Gf+znyj78HgOTsiA0jFIYdEY3CUNNxUG2nqM7N6UbxvabofOEL8La3daIfIhrt5eGH9fH55+m/7cbWFrz4ImdH3sChQ7pWUnCX93xQLzT/vz9Ye/WL3/ym7qX6L/4FhMOcOaPv2eHDDg9SuIkjR/Q9+OsLhyEU6l80rq/z7fVZjh3ctXaAwl1pO6haJRqLyzpLIHZIHqhO84Y3aC+FZ5vf3X2kcWcHPvhB+LVfg5/7OV7+yV8F5Lkq9IeIRmGoOXJEOy+++GLrC3Nz+nj9evcnee45Hap83/s4e1bXFrR1jGAPBw7ogNPzz6OVw4EDvYvG55+HRoOz1XlJTfUIr3/3AebUEp9/5jbumb/6qxCJwC/8AqA/sydP6pYPgru84x3wlWd8NN/0eN+iMf+5v+UK8zz2tnGLRyfcjYUFOH8ezHhCP0sHjTRmtOgX91TnCQTg8cfhmY1HuhONpgnvfS98+tNaNP7Gb/DlZ/xMT+taZUHoFfnUC0ONz6ejgp1I48GWXXUvZjgf/7hWnh/8IGfP6g3bcVn32IpStzHD6VU0njpFHT8vL09JZNgjKJ/ifTOn+Nyl1/JH/8+KrlUFvSnzx3+se8xFIpimTk2W1FRv8OSTUCzCmRM/oiPCfZipPPeHuib50fcftHp4wl1YWNA+bssryhIH1VJBO+DGxQDXFZ54Al4ozrGe2dai8G5cvqxLa375l+GXfgkTxVe+At/7vXqOFYRecUQ0KqVGlVKfUEpdUUptKqW+pZR6d+u1eaWUqZQq7/nzkVve+9+VUhtKqVWl1L+85dzvVEq9rJSqKqW+pJSSoLtwEydP3pKeCt3XNZbL8Pu/Dz/2YxCNinOqgzzyiL5v9To3ROO9Jsm9nDrF+dT3sLurJNLoIT7291/kTXyDv//PDD4Z+ln9gXr/+/VOzC/+IqD1Y6kkotErtOsa/1q9ExoN+PrXez7H6b/V7sdvfFxqqZyk7aB6/jw69ebSpYHOVyopAqouLadc4oknwMTH3za+Sz8k78ZXvqKP738/oL3krl/XolEQ+sGpSGMAuAa8HYgAHwH+UCk1v+d7oqZpTrT+/PKer38UWAAOA08Cv6SU+n4ApVQS+J+t88WB08BnbP2fCPuOkydhdRXyeXSaI3QvGj/zGW3h+aEPsbura0NENDrDI49ok81z59CicWND38huOXWKlw7/ACD3zEtE/49/z1N/6eedr13lZxqf4L/4/rm2ePzoR1mtJ/nRH4Uf/VEtGH/kR9werQB6r21hAb507ZhO3+i19cbSEs/lD7GQLBEV/xRHuW2vxl42326htBkgNlqVSJVLvPnNEPA3eYYn7m2G8/TTOiTccoH78pf1l9/+dnvHKAwvjohG0zQrpml+1DTNy6ZpNk3T/DxwCXi0i7f/JPDLpmmWTNP8DvBx4Kdbr/094Kxpmp81TXMbLTAfVkpJxZnQod3n7exZtJFDMtm9aPz4x/UD93u+h3PndNRLBIgzDGSGs7EBr7zC2cnHUQoeesiWIQr9EAgQfufjfO65A/zQD8EvvvQhPvaBs3wy9a95zWvgc5/TJqqnT4NhuD1Yoc2TT8LTfxOk/vo39l7X+MUvcprHePQxURpOc/AgjIzsEY3b271tvu1ld5fS1iix8R1Lxyh0TzgMb1zY1KLxXnWNTz+tQ5OtwvAvfxnSaXjgAfvHKQwnrtQ0KqXSwAng7J4vX1FKLSml/t9WBBGlVAyYBV7Y830vAO1l+2v3vmaaZgW4sOd1Qbi9g2o3ovGFF3Qa1oc/DEpp0YmIRqd48EGdsfj00/TeduO55wA4Wz8hNageZXQU/vAP4Sd+Aj7yEfiZn9Gfreefh3//73XwUfAOTz6p92K+ufD34W//Fmq1rt+b/fw3uMYhHnvnbQyQBFvx++HYMXjlFQZ3UH36aUpmlFjSb9n4hN554s01vsGb2FnK3fmbrl/X+aitsKJpIvWMwsA4LhqVUkHg94BPmab5MpAHvgudfvooMNl6HWCidVzfc4r11ve0X9/72q2v773uh5VSp5VSp3O5u3zQhKFjZgZisVvMcLoxwvn4x/XK9id+AtCRSp9PnFOdIhiEH/ohnSG8nTgAExPdRxpPnQLgpUxKRL6HCQTgk5/Uxqm/9Vt6USOfL2/S6dcYfJd2Vum4VN2DZpPn/kq3WJFIozu84Q2tfbRBRePnP09RJYkdFvHvJm/93gA7hDj93F2+qZ1C/ra3AfqWLy1JaqowGI6KRqWUD/gfwC7wCwCmaZZN0zxtmmbdNM1M6+vvUkpNAW2Ltqk9p5kCNlt/L9/y2q2vdzBN87dN03zMNM3HUqmUZf8nwfsodRsznHtFGqtV+N3f1UVVLZu4s2f1jm0oZO94hRv81E/ptpqf+7zqzUH11Cl250+weDEgJjgex+eDf/fvdEBf2mt4l3RaZ+p/afmE/kK3KaovvcTpde3v/8Y32jQ44a686U16ylsOtnwC+zHDMU343Ocojc1IpNFl3vpuHRd55vlbl797ePpp3WKlVefRrmcUExxhEBybopVSCvgEkAZ+2DTNO+W2tCu0lWmaJWAFeHjP6w9zI6317N7XlFJh4Bg3p70KAidP6r5vpokWjcWiFoZ34rOfhfV1+NCHOl8S51Tnecc79O365CfpXjTW6/DVr3LugR+UGlRBsJAnn4RnT4XYPfog/NVfdfemL36R53iUB47VmLrLGlewjze9SR+/cSakzeD6iTR+5ztw8SIlFZd2Gy6TTPt5yH+OZ87P3Pmbnn4a3vIWnc6BFo2GIZkcwmA4ua/7m8BDwA+aprnV/qJS6s1KqQeUUj6lVAL4L8CXTdNsp53+DvAflFKxlsHNh4BPtl77E+CkUuqHlVIh4D8CZ1ppr4LQ4eRJrQGvX+dG243r1+/8ht/+bThxopPasbOjLctFgDiL36+zg7/wBVg58JhOK75Xj7g/+RNYWeGlkz8OyD0TBKt4xzugUoFTj/1j+OIX9UP1Xnzxi5wOPM6jb5YiVbd4wxu0dvjGN+i/V+PnPkcTxdrWKLGY5UMUeuSJyAt8deUozeZtXszn9S53a/0i9YyCVTjVp/Ew8LPAI8Dqnn6MHwSOAn+BTil9CdgBPrDn7f8JbW5zBfgK8Oumaf7/7d15mFTVmfjx78siENkEDcgmUURFjSugROKexKiJxvyyuAST0bjEuA+jjmMSo/4mY0YnPnGZxCXumhij4jZoXEgCChgBwSAGRR1ZorIIiiJw5o9z0abpKhptuqqp7+d5+qnue2/dfunDrar3nvec8zBASukN4AjgYmABMBT4VnP8m9SyrDYZztrWapw2DcaO/XACHMiTCKxYYQJSCSNG5L/9rbOLQVUzZpR/wmWXwVZbMa3drrRu7UxxUlPZe+/8kvh418Nh2TK4777yT3j/feY++QKvL+/J7rs3T4xaU/v2uUrx6af5REnjzO0OZeXKoH//po5Q62r/3tNZtHxj7rmngZ2rSseLpPHll/P9Vscz6pNqriU3XkkpRUqpfZ21GDumlG5NKd2eUvpMSmnjlNLmKaXvpJTm1nnu+yml76WUOqeUeqSULqt37kdTStumlDqklPZJKc1qjn+TWpZVyd5qSWOpyXB+85s8C8t3vvPhJmdOrZxttoE99oAbnxqYa9fLlaiOGwdPPQWnn87U51sxYIBjUKWm0r17Xj/z8b/3gX798vS35YwdyzPv5TXidmvMAltab4YMyfODrey/Za6yee+9xj/5zTdh3DieHXQUkHsuVVlf234G27edwciR+f7NasaMyW98xZ0axzOqqTjtgGpC9+55FtVG9TSOG5ffYetMmDRtGvZaVdCxx8LUF9vz19i9/LIbl10GXbvCscc6BlVaD/bbD/7yl+C9w76V68YXLix98KOP8kwMJiKZaFTY0KGweDG80L6YBuKVVxr/5AcfhJUrmdRpOG3a+LpaDdpsvhk/bzWSmTPhyivr7RwzJt9pbdcOyEnjZpu5XrE+OZNG1YwddyySxk99Ks+I2lDSuHIlTJkCO++82uZp02DAgA9fg9XMvvnN/Lf/Tecflu5pnDUL7r4bTjiBpa07MnMmzpwqNbF9981jvJ/aZkReq7FcieojjzCx6wFsu23QaY2FsNScVk2G8/Ti3PO7TiWqo0bB5pszaW5PBg3yfbAq9OjBl96/ly8esJyf/jTP7QfkxVSffXaN8YyrSsulT8KkUTVjhx3g+efz+LiSy268/HK+HVsvaZw61burldS1Kxx2GNz27mG8//zMhg+64oq8ZsMppzB9es7/bTOpaX3+8/kye2zOduVLVOfPh4kTmfjBTpamVoFttoHOnWH8673yhsYmjcuW5R7lgw9m0uSo/9aoStkiL5/y8/0eYtEiuPDCYvvYsfnNr0gaZ82CV1+1NFVNw6RRNWOHHWDp0mKJqlJJ4+TJ+XGnj1Z5eeaZPHOqL7qVNWIEzP+gMw/MGFBk/nUsWgTXXpu7JPv0+XAMqj2NUtPq0gX22guuvyF497AjYfTohktUR49mdurJnCWdnASnCrRqBYMHw9PPfSqPd2ts0jhmDCxezLzhX2fOnDXup6pSjjgChg9nhwu/wXGHvcmVVxZzxI0Zk6fK3WMPwPGMalomjaoZqxKI554jJ40NTYQzaVJ+d62TbVx5JWy88Wrz4qgCDjwQNu/yLjcuPwruvJPV5hq/7rrcQ3zGGUAuJ27bFrbeukLBShuwiy/Oc6n853s/yCWq9967+gHz58M//zPP9PoK4CQ41WLIEJgyJVjaf7vGJ42jRkH79kzqkqfeNGmsEm3b5vWkN92UC8d/ifbtVvIv/0KuRd199/yhhZw0bropDBpU0Wi1gTBpVM0YNChPZvPYY0DfvnlGuPozyE2enOt4OnQA4K234Pbb81qBXbo0f8z6SJs2cMxRK3iAg3n1qHPyINUbb8zdx7/4RR60UXw6nTo1L7PZ1qXhpCa3117wta/Bz27tnddPrVuimhKccALMm8czB19Aq1YmGtViyBBYvhwmdduvKLlZi5Ry0rj//kyanqehti2rSI8ecPfd9HhjKuf2uIF77oF7nt6cJ/uP4NprYeRIuP9+xzOq6Zg0qmas6i389a/h1Q7FNKivv776QZMnr1aaev31Oa/8wQ+aMVCVdMJZnejQsTWH93+Wd6Jjnla1V688aOPMM4HcpE89ZWmqtD797GewbFlwQbdfwiOPwIIFecf118Ndd8FFFzFxdi+22w46dqxsrMqGDs2PT7celnsaUyr/hOefz8nloYcyaVIeRrfJJus/Tq2DwYPhmms446VT6NtuHoevuIt97jiR44/Pw/x79cpLTktNwaRRNeXHP87vkz95dFjeUHdc44IFeRry4lbqihVw9dX5Lp0JSHXYcku4445g0qvd+c42T7Hy/gdze+21FxxyCPPmwf7759kdR46sdLTShmvAADjlFLhu6hCmfLBtLlGdMQNOPRX224901tlMnGhpajXZfPM8MmP8O4NyOf9bb5V/wqhR+fGQQ5g0yV7GqnXssXT4wT9xz/sH8UtOYfTdS5g1C959Nw/H+cIXKh2gNhQmjaop/frlXsPfjO7F39h29aRxypT8WPQ0PvRQvslqL2N1Ofhg+PnP4e67g38bexA8/jj86U/MX9iKAw/MnY4PPAC77lrpSKUN2/nn55mNz25/JenmW+DII/MkKzfdxOy5rZg3DyfBqTJDhsD42X3zD2sb1zh6NOy0E+907c0LL5g0VrXLL2fXfbvyg+FTOPDwjmyxRZ6eQWpK/pdSzTn33Fyqej4XrT4ZzqRJ+bF4Z7zyylzacdhhFQhSZZ1+Ohx/PFxyCdx8c5489YtfzB0d990Hw4dXOkJpw9etG/zoR8Ej7w3n4cfa5qmmr7uOxZ17c9NN+Rh7GqvL0KEwc+7GvEl3mFli+SLIE41NnAjDhvHcc7lCZ5ddmi9OraO2bXOS/8c/VjoSbcBMGlVzNtsMzjoruJsjGP9M6492TJ4Mn/409OzJiy/Cww/n+RycTKX6ROSkft994bjj8nTikybloVQHHFDp6KTacdJJMKDve5zFf3LFsDv4wlWH0b07nHdeLoU00aguQ4bkxwmt98yLwJfywgu5hHXIkPr3U1Wt2rTxA4vWK5NG1aQzz4RNW8/nvCfqFPvXGbRx9dX5tdcB5NWrbducJG6xRa4svu02OOSQSkcl1ZaNNoL/+EV7/sYgThv7TV57DU47LU/1/9JLH05ErSqx2275ptv4nl+BceNKHzhhQn4cPJhJk3IZcr9+zROjpOrUptIBSJXQqROcv/VvOX36iTz6KByw9wd5cb/TTuOdd/IEgEccAT17VjpSldOtG/zpT7nK2LFTUmUcdhj8z//kiaoGDKh0NCqnUyfYfnt4esnnYOKpsGxZzvzrmzAhj+PYdtsP76e6bINU2+xpVM06cc/J9Gv1v5x9Nlx7yT+4fNnJ/PTlo/nud/MYuVNOqXSEaowePUwYpUqKyDM0mjC2DEOGwPi3tiK9914eltGQ8eNht91YQWumTLHMWJJJo2pYuy16cvHKc5g8GY7/cW/O5HIuuOuzjBoFBx0Ew4ZVOkJJkprW0KHw1uJ2vMxnGi5RXbYsD9cYPJgZM2DpUsczSjJpVC3r04ejuJWZT7zGq9+/iAUb9WDZu8tZuhQefNBSHEnShmfVZDhjun614aTxuedy4ugkOJLqMGlU7erblwC2bDWLvi89Sdcd+9K2g8N8JUkbrh13hIED4Qp+SBrbQNJYbxKcjTaC7bZr3hglVR+TRtWuPn3y42uv5XEdO+1U2XgkSVrPWreGc86BZxduyUOvDoI5c1Y/YMIE6N4d+vfn2Wdhhx1cyUGSSaNq2aqkccIEeOMN628kSTXh6KOhX4/3uZh/XbO3cfx4GDyYRNRdiUpSjTNpVO3q3DnPP/7AA/lnexolSTWgbVsYeW4rxvI5nvztvI92vPMOPP88DB7MnDneT5X0EZNG1bY+feDFF/P3Jo2SpBrxve+3pUfbt7hk9G4fbfzrX2HlytUmwXG5DUlg0qha17dvfuzfH7p0qWgokiQ1lw4d4Mw9xvHIwiFMGPtB3lhvEhyAz362MvFJqi4mjaptq8Y1Wn8jSaoxJx2/nE2Yz8XnLskbxo+Hvn2Z+kYPbr0Vttoqj+SQJJNG1bZVSaOlqZKkGtNpv8GcyhXcO2YTnnsOFj39N07f6Cp23hnmzoVLL610hJKqhUmjaps9jZKkWtW7N6f2+j0d2yzln0YsZ+Cs0Vzx0sEcdxzMmAGHH17pACVVC5NG1ba994bPfQ6GD690JJIkNbtuew3i5A6/YcKzbfgMLzPhqolcc01eqlGSVjFpVG0bOBD+/GffHSVJtWnPPblw8ek8/pXLGcswdvv2wEpHJKkKtal0AJIkSaqQPfekHcvY59HzYZuBziQuqUH2NEqSJNWqXXaBdu3g3Xdh8OBKRyOpSpk0SpIk1aqNNoLddsvfDxlS2VgkVS2TRkmSpFq255750Z5GSSU4plGSJKmWjRiRF2bcdddKRyKpSpk0SpIk1bIdd4Rbbql0FJKqmOWpkiRJkqSSTBolSZIkSSWZNEqSJEmSSjJplCRJkiSVZNIoSZIkSSrJpFGSJEmSVJJJoyRJkiSpJJNGSZIkSVJJJo2SJEmSpJJMGiVJkiRJJZk0SpIkSZJKMmmUJEmSJJVk0ihJkiRJKsmkUZIkSZJUkkmjJEmSJKkkk0ZJkiRJUkkmjZIkSZKkkkwaJUmSJEklRUqp0jE0u4h4A3jlYz69H/BqE4aj5tcFWFTpIPSx2X4tn23Y8tmGLZ9t2LLZfi1fNbThNimlTo05sM36jqQapZQ2+7jPjYg3Ukq7N2U8al4R8auU0vcrHYc+Htuv5bMNWz7bsOWzDVs226/lq4Y2jIiJjT3W8tR1t7DSAegTG1XpAPSJ2H4tn23Y8tmGLZ9t2LLZfi1fi2rDmixP/SQiYqI9jZIkSZJasnXJa+xpXHe/qnQAkiRJkvQJNTqvsadRkiRJklSSPY2SJEmSpJJMGrXBiohuEfGHiHgnIl6JiCOL7QdHxJ8jYmFEzI2IX0dEo6YbVvMq04b7RsRzRRu+VRzTu9LxanWl2q/eMTdERIqIAZWIUeWVuaG99AgAAAxTSURBVAb3iYiVEbGkzteISserNZW7DiNis4i4rXgtXRARt1YyVjWszHV4Xr1rcGlxXW5a6Zj1kbVcgz+MiJcj4u2ImBgRe1Uy1nJqcskN1YwrgWVAD2Bn4IGImExeF+ciYAzQDrgNuBQ4sUJxqrRSbfg88MWU0uyIaAf8FLga+ErFIlVDGmy/lNI0gOLNcasKxqe1K3UNAsxOKfWpWGRqrHLX4d3ABGAL4F1gh4pFqXJKteElwCWrDoqIHwOfTym9WZEoVUqp19GOwL8Dnwf+Sv4c+oeI6JlSWlGpYEtxTGMJEdENuA74AvAmcG5K6baI2Bz4b2B3YHPgMymlWRULVA2KiI2BBcAOKaUZxbabgddTSufUO/ZrwE9SSjs2f6QqpbFtWCSNPwa+mlIaVIlYtaa1tV9EtCF/WB0BTAa2Tin9vWIBaw3l2hB4GLjFpLG6raUNHyNPgrFVNX5AVbYO74UB/B24MKV0Y0WC1RrWcg0+C5yVUhpS59glQK+U0pwKhVyS5aml1b0rcBRwdURsD6wkv1keUcHYtHYDgRWrLtDCZGD7Bo79PDCtWaLSuijbhhHRLyIWAkuBs4H/aP4QVcbarsEzgDEppSnNHpkaa21t+OmImFeUVl1efOBRdSnXhnsALwA3FmX+EyJi70oEqbIa+3lmOPkz6++bKzA1Srn2ewhoHRFDI6I18D1gEjC3+cNcO8tTG1C88R1BviuwBPhzRNwHHFPc1bmquEuu6tURWFRv2yJgtbGLEXEguadjaDPFpcYr24YppVeBrkVVwPHA9OYNT2tRsv0ioi9wArBbs0eldVHuGpxOLrOaTi5tvBG4jNyuqh7l2rAPuZrqOOC75M8990bEAMsbq0qjPs+QP8vcVXxuVfUo136LyUn+n4EAFgIHpSotA7WnsWHr0kul6rQE6FxvW2fyBQpAROxBHs/49Xptreqw1jYESCnNJ39gvdebOVWlXPv9F7mEqv4bqapLyTZMKc1NKT2fUlqZUnoZGAl8vdkj1NqUuw6XArNSStellD5IKd0BvAZ8rpljVHmN+TzTAfh/5PdCVZdy7XccuXdxe2Aj4Gjg/ojo1awRNpJJY8Mae1dH1WsG0CYitq6zbSeKMtSI2AW4D/heSumPFYhPa1e2DetpA3yaNV+YVTnl2m9/4NLIsxevKsMZ19DsqqqodbkGE/lOuapLuTacQm43VbfGXIdfA+YDTzRjXGqccu23EzAqpTSjuAH3MDAHGFaBONfKiXAaUCQUf0kpfarOtrOAfVJKhxY/twE+wIlwqlZE3EF+QzyOXEb1IPlCDOCPwKkppTsrF6HWpkwbbkN+wX0R6E4egzwgpbRrhUJVA8q03xusftNyDrAnMDmltLS541RpZdpwM+Alcs9UH+Amcq/VdysUqkoo04ZzgJnA6cAtwOHkiXEGWp5aXUq1YZ2ZqEcDT6WULqhclCqlzDW4O/CvwJeAl4EDgHuBXVNKVTfkxp7Ghq3L3VVVr5OBDsA/gNuBk4oX2LPIH3iuq7O2kW1bnUq1YW/yhFSLgefIE1QdXqkgVVKD7ZdS+kdR3jg3pbSqp/FNE8aqVOoa3BUYB7wDjAWmAqdWKkiVVeo6nE9epuhscjXVOeRZqE0Yq0+p65DIaxTvR75xo+pUqv1uAu4g9xC/DVwBnFCNCSPY01hSubs6EdEeaE2uU94WeCWl9F7FgpUkSZKk9cSksYRiRsbrgQOBt4BzUkq3FfvW+KOllBzLIUmSJGmDY9IoSZIkSSrJMY2SJEmSpJJMGiVJkiRJJZk0SpIkSZJKMmmUJEmSJJVk0ihJkiRJKsmksRARsyJiXkRsXGfbcRHxRAXDkiRJkqSKMmlcXRvgtEoHIUmSJEnVwqRxdZcCZ0dE1/o7ImJYREyIiEXF47Bi+7ciYmK9Y8+IiPuaKWZJkiRJWm9MGlc3EXgCOLvuxojoBjwAXAF0By4DHoiI7sB9wDYRsXWdpxwJ3NYcAUuSJEnS+mTSuKYLgB9GxGZ1th0MvJhSujmltDyldDswHTg0pfQucC/wbYAiedyWnExKkiRJUotm0lhPSmkqcD9wTp3NvYBX6h36CtC7+P42iqSR3Mt4T5FMSpIkSVKLZtLYsB8Bx/NRUjgb2KLeMf2A14vvRwObRsTO5OTR0lRJkiRJGwSTxgaklP4O3AmcWmx6EBgYEUdGRJuI+CYwiNwjSUppOXAXeSKdbsAjzR+1JEmSJDU9k8bSLgQ2BkgpvQUcApwFvAWMBA5JKb1Z5/jbgAOA3xVJpCRJkiS1eJFSqnQMkiRJkqQqZU+jJEmSJKkkk0ZJkiRJUkkmjZIkSZKkkkwaJUmSJEklmTRKkiRJkkqq2aQxItpFxHUR8UpELI6IZyPioDr794+I6RHxbkQ8HhFb1Nn3jYgYW+x7oszvGBERKSKOW8//HEmSJElaL2o2aQTaAK8BewNdgH8DfhsR/SNiU+DuYls3YCJwZ53nzgf+C/j3UiePiE2Ac4Fp6yV6SZIkSWoGrtNYR0RMAX4CdAeOTSkNK7ZvDLwJ7JJSml7n+OOAo1NK+zRwrmuAKcA3gFtSSteu/3+BJEmSJDWtWu5pXE1E9AAGknsGtwcmr9qXUnoHmFlsb8y5hgC7A9c0faSSJEmS1HxMGoGIaAvcCtxY9CR2BBbVO2wR0KkR52oNXAX8MKW0sqljlSRJkqTmVPNJY0S0Am4GlgGnFJuXAJ3rHdoZWNyIU54MTEkpjWuyICVJkiSpQtpUOoBKiogArgN6AF9OKX1Q7JoGjKhz3MbAVjRuUpv9gb0j4svFz92AXSJi55TSKWWeJ0mSJElVp6aTRuBqYDvggJTS0jrb/wBcGhFHAA8AF5B7D6fDhyWobcl/v1YR0R5YUSSdxwLt65zrbuAucnIqSZIkSS1KzZanFusungDsDMyNiCXF11EppTeAI4CLgQXAUOBbdZ5+DLCUnHQOL77/NUBKaWFKae6qL3LZ69sppfpjJCVJkiSp6rnkhiRJkiSppJrtaZQkSZIkrZ1JoyRJkiSpJJNGSZIkSVJJJo2SJEmSpJJMGiVJkiRJJZk0SpIkSZJKMmmUJAmIiH7Fer2tKx2LJEnVxKRRklSzImJWRBwAkFJ6NaXUMaW0ohl//z4R8b/N9fskSfo4TBolSZIkSSWZNEqSalJE3Az0A0YVZakjIyJFRJti/xMRcVFEjC32j4qI7hFxa0S8HRETIqJ/nfNtGxGPRMT8iHghIr5RZ9+XI+L5iFgcEa9HxNkRsTHwENCrOP+SiOgVEUMiYlxELIyIORHxy4jYqM65UkScHBEvFuf7aURsVTzn7Yj47arjV/VkRsR5EfFm0bN6VPP8hSVJGwqTRklSTUopHQO8ChyaUuoI/LaBw74FHAP0BrYCxgE3AN2AvwE/AigSwEeA24BPA98GroqI7YvzXAeckFLqBOwAPJZSegc4CJhdlMV2TCnNBlYAZwCbAnsC+wMn14vrS8BuwB7ASOBXwFFA3+L8365zbM/iXL2BEcCvImKbdfpjSZJqmkmjJEml3ZBSmplSWkTuFZyZUno0pbQc+B2wS3HcIcCslNINKaXlKaW/Ar8Hvl7s/wAYFBGdU0oLiv0NSik9k1J6qjjPLOC/gb3rHfazlNLbKaVpwFRgdErppTpx7lLv+H9LKb2fUnoSeAD4BpIkNZJJoyRJpc2r8/3SBn7uWHy/BTC0KCldGBELyT1/PYv9RwBfBl6JiCcjYs9SvzAiBkbE/RExNyLeBi4h9xR+nLgAFhS9mqu8AvQq9fslSarPpFGSVMtSE53nNeDJlFLXOl8dU0onAaSUJqSUvkouXb2Hj0phG/r9VwPTga1TSp2B84D4BLFtUpTPrtIPmP0JzidJqjEmjZKkWjYP2LIJznM/MDAijomItsXX4IjYLiI2ioijIqJLSukD4G3yuMVVv797RHSpc65OxTFLImJb4KQmiO8nRRzDyaW0v2uCc0qSaoRJoySplv1/4PyinPTrazu4lJTSYuAL5IlzZgNzgZ8B7YpDjgFmFeWmJwJHF8+bDtwOvFSUtfYCzgaOBBYDvwbu/LhxFeYCC4q4bgVOLH6vJEmNEik1VWWOJEmqJhGxD3BLSqlPpWORJLVc9jRKkiRJkkoyaZQkSZIklWR5qiRJkiSpJHsaJUmSJEklmTRKkiRJkkoyaZQkSZIklWTSKEmSJEkqyaRRkiRJklTS/wEylt7Pl+L+EgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "eval_df[eval_df.timestamp<'2014-11-08'].plot(x='timestamp', y=['prediction', 'actual'], style=['r', 'b'], figsize=(15, 8), fontsize=12)\n",
    "plt.xlabel('timestamp', fontsize=12)\n",
    "plt.ylabel('load', fontsize=12)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
